Name	Completeness	Contamination	Contig_Number	Contig_Names	Contig_Lengths	Contig_Depths	Avg_Depth	Status	Completeness_Model_Used	Translation_Table_Used	Coding_Density	Contig_N50	Average_Gene_Length	Genome_Size	GC_Content	Total_Coding_Sequences	Additional_Notes	Old_Bin_ID
MAG1	100.00	1.20	1	s76.ctg000116c	2099507	155.318	155.3	Pass	Gradient Boost (General Model)	11	0.872	2099507	325.7931	2099507	0.41	1875	None	s76.ctg000116c
MAG2	13.01	0.05	1	s0.ctg000281l	436803	116.911	116.9	Fail	Neural Network (Specific Model)	11	0.862	436803	293.8084	436803	0.42	428	None	bin.245
MAG3	99.96	0.95	1	s159.ctg000256c	2957114	113.604	113.6	Pass	Neural Network (Specific Model)	11	0.904	2957114	329.8833	2957114	0.44	2707	None	bin.12
MAG4	28.19	0.05	1	s0.ctg000391l	1000597	111.448	111.4	Fail	Neural Network (Specific Model)	11	0.882	1000597	306.5546	1000597	0.42	961	None	bin.211
MAG5	100.00	0.34	1	s42.ctg000061c	3316695	101.833	101.8	Pass	Neural Network (Specific Model)	11	0.875	3316695	311.4859	3316695	0.41	3110	None	s42.ctg000061c
MAG6	12.33	0.03	1	s0.ctg000593l	469361	98.2859	98.2	Fail	Neural Network (Specific Model)	11	0.843	469361	279.3742	469361	0.41	473	None	bin.218
MAG7	99.16	0.23	1	s138.ctg000209c	2310828	88.2841	88.2	Pass	Neural Network (Specific Model)	11	0.865	2310828	348.0563	2310828	0.60	1917	None	bin.26
MAG8	98.71	1.75	1	s1189.ctg001734c	1799175	82.1033	82.1	Pass	Gradient Boost (General Model)	11	0.866	1799175	277.7953	1799175	0.27	1876	None	bin.52
MAG9	98.96	13.12	25	s0.ctg000085l,s0.ctg000115l,s0.ctg000153l,s0.ctg000801l,s0.ctg000842l,s0.ctg000857l,s0.ctg000904l,s0.ctg001094l,s0.ctg001160l,s0.ctg001292l,s0.ctg001597l,s0.ctg001600l,s0.ctg001853l,s0.ctg002172l,s0.ctg002193l,s0.ctg002756l,s0.ctg003100l,s0.ctg003148l,s0.ctg003376l,s2831.ctg003686l,s3051.ctg003927l,s4085.ctg005094l,s4342.ctg005376l,s0.ctg006649l,s0.ctg010623l	107901,86440,243408,103419,84872,951337,67385,124993,300956,296560,79412,265847,668906,91483,88204,92148,59878,95872,58050,38179,36860,66361,98028,41478,42954	89.4636,90.3264,83.2696,72.7766,67.4538,102.255,79.4895,121.363,103.661,72.6463,80.711,68.1464,93.1313,105.639,96.6525,72.5961,67.4345,90.607,110.337,59.8571,52.6522,96.6639,31.1498,60.5935,81.7612	82.0	Fail	Neural Network (Specific Model)	11	0.855	296560	318.4460	4190931	0.41	3758	None	metabat2_bins.198
MAG10	99.99	0.67	1	s0.ctg000046l	2548956	79.5644	79.5	Pass	Neural Network (Specific Model)	11	0.872	2548956	303.4618	2548956	0.34	2445	None	bin.2
MAG11	97.99	3.16	4	s0.ctg000493l,s0.ctg000813l,s0.ctg001142l,s0.ctg001257l	839260,1004605,565691,193075	76.6338,67.4266,81.8162,71.2069	74.2	Pass	Gradient Boost (General Model)	11	0.889	839260	297.7440	2602631	0.34	2598	None	bin.45
MAG12	98.94	1.21	1	s113.ctg000172c	3173188	60.5649	60.5	Pass	Neural Network (Specific Model)	11	0.885	3173188	338.5437	3173188	0.44	2768	None	bin.16
MAG13	99.91	0.38	1	s95.ctg000142c	2387542	58.5194	58.5	Pass	Neural Network (Specific Model)	11	0.861	2387542	335.2633	2387542	0.60	2047	None	bin.38
MAG14	100.00	0.14	1	s110.ctg000166c	2043995	58.349	58.3	Pass	Gradient Boost (General Model)	11	0.902	2043995	328.3803	2043995	0.53	1875	None	s110.ctg000166c
MAG15	43.38	0.08	1	s62.ctg000425l	957331	57.7865	57.7	Fail	Neural Network (Specific Model)	11	0.855	957331	384.5563	957331	0.60	710	None	bin.124
MAG16	99.98	0.13	1	s30.ctg000042c	3684995	57.0711	57.0	Pass	Neural Network (Specific Model)	11	0.836	3684995	355.5328	3684995	0.45	2892	None	bin.20
MAG17	31.52	0.39	2	s0.ctg001421l,s0.ctg001538l	407530,614245	55.5148,52.6775	54.0	Fail	Neural Network (Specific Model)	11	0.862	614245	309.2839	1021775	0.41	951	None	metabat2_bins.81
MAG18	9.51	0.06	3	s1587.ctg002229l,s3245.ctg004145l,s0.ctg004316l	140278,142434,54723	44.0869,44.3105,54.627	47.6	Fail	Neural Network (Specific Model)	11	0.859	140278	304.4717	337435	0.41	318	None	metabat2_bins.15
MAG19	99.94	1.37	3	s0.ctg000001l,s439.ctg000685l,s0.ctg001198l	1133714,1314508,1037969	46.1949,38.0421,51.4915	45.2	Pass	Neural Network (Specific Model)	11	0.867	1133714	319.4679	3486191	0.44	3161	None	metabat2_bins.304
MAG20	90.28	0.14	2	s0.ctg000016l,s0.ctg000460l	979643,2602119	43.1161,46.1004	44.6	Pass	Neural Network (Specific Model)	11	0.880	2602119	326.9475	3581762	0.47	3219	None	metabat2_bins.325
MAG21	32.96	0.04	1	s176.ctg001250l	631897	43.5513	43.5	Fail	Neural Network (Specific Model)	11	0.863	631897	363.9340	631897	0.60	500	None	bin.149
MAG22	87.91	1.40	9	s0.ctg000163l,s0.ctg000427l,s0.ctg001354l,s0.ctg001654l,s0.ctg001864l,s0.ctg002645l,s0.ctg003116l,s2618.ctg003436l,s835.ctg004870l	517214,378799,63249,629425,671381,148068,146808,226383,133124	45.1473,48.5678,26.4705,52.7555,42.3068,39.5691,39.7912,40.1835,57.1328	43.5	Pass	Neural Network (Specific Model)	11	0.839	517214	318.5326	2914451	0.55	2565	None	metabat2_bins.401
MAG23	99.98	0.67	1	s434.ctg000680c	2422410	43.0232	43.0	Pass	Neural Network (Specific Model)	11	0.869	2422410	330.1448	2422410	0.60	2127	None	bin.27
MAG24	99.73	0.37	4	s18.ctg000158l,s18.ctg000736l,s18.ctg000787l,s18.ctg005096l	1695507,1400710,1439177,108223	40.8336,41.9794,48.7962,37.201	42.2	Pass	Neural Network (Specific Model)	11	0.901	1439177	350.3787	4643617	0.46	3985	None	metabat2_bins.298
MAG25	100.00	1.69	2	s50.ctg000072c,s176.ctg004356l	2323001,102258	45.5063,37.5522	41.5	Pass	Neural Network (Specific Model)	11	0.870	2323001	355.1337	2425259	0.57	1982	None	metabat2_bins.309
MAG26	99.89	0.53	6	s0.ctg000089l,s0.ctg000092l,s0.ctg000364l,s0.ctg000384l,s0.ctg001176l,s0.ctg002966l	657474,386865,213633,377706,977074,259528	42.9249,49.933,36.4053,49.0666,37.7852,32.5002	41.4	Pass	Neural Network (Specific Model)	11	0.871	657474	318.6127	2872280	0.41	2621	None	metabat2_bins.420
MAG27	95.00	1.57	1	s0.ctg000043l	2481855	40.2514	40.2	Pass	Neural Network (Specific Model)	11	0.880	2481855	339.9977	2481855	0.41	2144	None	bin.9
MAG28	100.00	8.61	8	s0.ctg000274l,s0.ctg000413l,s0.ctg000711l,s0.ctg000784l,s0.ctg000895l,s0.ctg001111l,s0.ctg003991l,s6271.ctg007492l	1770195,540419,577318,1029803,188643,558763,149793,66370	38.3601,39.5413,39.8777,41.5738,36.404,39.0596,32.9121,48.6395	39.5	Pass	Neural Network (Specific Model)	11	0.863	1029803	313.4329	4881304	0.43	4488	None	metabat2_bins.254
MAG29	99.99	2.55	1	s247.ctg000394c	2548993	39.2929	39.2	Pass	Neural Network (Specific Model)	11	0.854	2548993	308.7833	2548993	0.37	2353	None	bin.10
MAG30	22.37	0.04	2	s0.ctg001785l,s0.ctg001945l	524649,161106	40.0968,37.2325	38.6	Fail	Neural Network (Specific Model)	11	0.836	524649	303.2409	685755	0.58	631	None	metabat2_bins.316
MAG31	70.73	0.10	1	s169.ctg000269l	2233352	37.5149	37.5	Pass	Neural Network (Specific Model)	11	0.880	2233352	314.9827	2233352	0.56	2084	None	bin.66
MAG32	52.71	0.38	1	s0.ctg000206l	1688387	37.2079	37.2	Fail	Gradient Boost (General Model)	11	0.846	1688387	331.7976	1688387	0.58	1438	None	bin.134
MAG33	68.73	0.66	1	s49.ctg000071c	2228948	36.1061	36.1	Pass	Neural Network (Specific Model)	11	0.874	2228948	326.1143	2228948	0.58	1994	None	bin.99
MAG34	46.65	0.00	1	s18.ctg000103l	2041876	33.7281	33.7	Fail	Neural Network (Specific Model)	11	0.895	2041876	386.2928	2041876	0.42	1578	None	bin.117
MAG35	22.35	0.11	3	s827.ctg001264l,s62.ctg001437l,s1591.ctg002233l	155538,315617,48912	35.7135,35.1492,30.4761	33.7	Fail	Neural Network (Specific Model)	11	0.881	315617	371.8929	520067	0.60	411	None	metabat2_bins.253_sub
MAG36	22.68	0.02	2	s18.ctg000539l,s18.ctg001329l	404814,256945	31.4703,33.4819	32.4	Fail	Neural Network (Specific Model)	11	0.862	404814	308.6564	661759	0.55	617	None	metabat2_bins.530_sub
MAG37	74.68	6.91	8	s18.ctg000215l,s18.ctg000459l,s18.ctg000598l,s18.ctg001253l,s18.ctg001931l,s18.ctg002570l,s18.ctg003503l,s18.ctg004208l	1128398,755166,297989,475545,362603,180897,207695,177436	32.9457,31.3209,31.5459,29.1004,31.1877,30.4957,28.4535,33.5011	31.0	Pass	Neural Network (Specific Model)	11	0.908	755166	357.7554	3585729	0.47	3038	None	metabat2_bins.184
MAG38	29.46	0.10	1	s176.ctg001820l	671491	30.5636	30.5	Fail	Neural Network (Specific Model)	11	0.866	671491	367.1686	671491	0.60	528	None	bin.153
MAG39	99.80	0.15	1	s39.ctg000057c	2063434	30.4416	30.4	Pass	Gradient Boost (General Model)	11	0.902	2063434	326.2310	2063434	0.53	1905	None	bin.0
MAG40	99.93	0.51	1	s133.ctg000200c	4413267	29.813	29.8	Pass	Neural Network (Specific Model)	11	0.903	4413267	355.6596	4413267	0.46	3740	None	bin.21
MAG41	44.74	8.50	3	s18.ctg000293l,s18.ctg000552l,s18.ctg002133l	1271232,544164,560354	30.3183,27.8096,31.0285	29.7	Fail	Neural Network (Specific Model)	11	0.896	1271232	379.9343	2375750	0.42	1871	None	bin.123
MAG42	99.99	3.87	1	s358.ctg000570c	3098954	29.1329	29.1	Pass	Neural Network (Specific Model)	11	0.872	3098954	314.1929	3098954	0.42	2872	None	bin.3
MAG43	99.35	0.17	1	s195.ctg000307c	1952197	29.0282	29.0	Pass	Gradient Boost (General Model)	11	0.909	1952197	335.6742	1952197	0.37	1765	None	bin.8
MAG44	23.80	1.91	2	s0.ctg000987l,s0.ctg001000l	547044,74251	28.9729,28.2939	28.6	Fail	Neural Network (Specific Model)	11	0.833	547044	320.4508	621295	0.58	539	None	metabat2_bins.514
MAG45	36.90	0.32	1	s18.ctg000372l	2160205	28.5244	28.5	Fail	Neural Network (Specific Model)	11	0.890	2160205	345.3093	2160205	0.43	1859	None	bin.131
MAG46	52.55	8.17	6	s18.ctg001604l,s18.ctg001790l,s2232.ctg002994l,s18.ctg003280l,s18.ctg003310l,s18.ctg003499l	353434,382292,108820,140270,192101,228473	24.1843,34.2316,21.1096,32.1939,29.2486,23.0008	27.3	Fail	Neural Network (Specific Model)	11	0.863	353434	318.8662	1405390	0.54	1271	None	bin.274
MAG47	26.29	0.25	1	s0.ctg000528l	955933	26.9562	26.9	Fail	Neural Network (Specific Model)	11	0.897	955933	329.0667	955933	0.42	870	None	bin.232
MAG48	99.88	0.52	1	s107.ctg000161c	3042723	26.5388	26.5	Pass	Neural Network (Specific Model)	11	0.862	3042723	311.7288	3042723	0.57	2810	None	bin.14
MAG49	99.99	0.81	1	s70.ctg000105c	3484333	25.862	25.8	Pass	Neural Network (Specific Model)	11	0.859	3484333	306.8962	3484333	0.56	3257	None	bin.19
MAG50	29.51	0.13	1	s18.ctg000692l	1192562	25.3882	25.3	Fail	Neural Network (Specific Model)	11	0.898	1192562	343.9606	1192562	0.57	1040	None	bin.200
MAG51	57.97	22.38	11	s18.ctg000028l,s18.ctg000208l,s18.ctg000409l,s18.ctg000973l,s18.ctg001062l,s18.ctg001206l,s18.ctg001220l,s18.ctg001380l,s18.ctg002421l,s18.ctg005742l,s18.ctg006900l	780470,479716,517681,165058,252449,142992,719229,234256,248531,82407,55016	26.517,25.3972,26.361,21.8828,23.0248,23.2163,22.4678,28.0415,27.2337,27.7688,24.9392	25.1	Fail	Neural Network (Specific Model)	11	0.907	517681	374.8166	3677805	0.47	2971	None	metabat2_bins.290
MAG52	98.08	2.06	2	s0.ctg000135l,s0.ctg000571l	1814298,740163	24.8721,24.2955	24.5	Pass	Gradient Boost (General Model)	11	0.891	1814298	316.5929	2554461	0.59	2400	None	bin.5
MAG53	51.34	0.20	1	s0.ctg000048l	1784060	24.0423	24.0	Fail	Neural Network (Specific Model)	11	0.860	1784060	326.8781	1784060	0.48	1567	None	bin.147
MAG54	99.90	0.25	1	s490.ctg000766c	1944142	23.6546	23.6	Pass	Neural Network (Specific Model)	11	0.867	1944142	358.6150	1944142	0.60	1569	None	bin.42
MAG55	20.81	0.03	1	s18.ctg000739l	810643	23.497	23.4	Fail	Neural Network (Specific Model)	11	0.906	810643	370.2251	810643	0.59	662	None	bin.204
MAG56	36.40	0.95	1	s0.ctg000452l	1225651	23.0836	23.0	Fail	Neural Network (Specific Model)	11	0.879	1225651	320.3722	1225651	0.41	1123	None	bin.190
MAG57	18.07	0.01	1	s0.ctg000025l	446873	22.9636	22.9	Fail	Neural Network (Specific Model)	11	0.859	446873	337.3079	446873	0.59	380	None	bin.237
MAG58	26.97	0.32	1	s0.ctg000540l	961333	22.8321	22.8	Fail	Neural Network (Specific Model)	11	0.898	961333	323.6128	961333	0.42	891	None	bin.233_sub
MAG59	100.00	1.80	1	s32.ctg000045c	3039924	22.7496	22.7	Pass	Neural Network (Specific Model)	11	0.870	3039924	327.5135	3039924	0.50	2697	None	s32.ctg000045c
MAG60	35.80	0.01	1	s0.ctg001129l	947765	22.6023	22.6	Fail	Neural Network (Specific Model)	11	0.882	947765	315.3729	947765	0.37	885	None	bin.197
MAG61	47.96	0.73	1	s222.ctg000347l	1286387	22.2658	22.2	Fail	Neural Network (Specific Model)	11	0.862	1286387	325.4556	1286387	0.58	1137	None	metabat2_bins.159
MAG62	89.01	2.02	5	s85.ctg000126l,s0.ctg001410l,s0.ctg001436l,s0.ctg002858l,s6251.ctg007467l	617782,1000037,878822,259716,26844	21.6944,24.7278,19.2117,24.6152,20.019	22.0	Pass	Neural Network (Specific Model)	11	0.840	878822	311.6579	2783201	0.54	2505	None	metabat2_bins.250
MAG63	77.88	13.40	1	s0.ctg000374l	3123679	21.3126	21.3	Fail	Gradient Boost (General Model)	11	0.864	3123679	316.8086	3123679	0.57	2847	None	bin.67
MAG64	26.21	0.17	1	s0.ctg001620l	979143	20.9011	20.9	Fail	Neural Network (Specific Model)	11	0.858	979143	321.1865	979143	0.43	874	None	bin.206
MAG65	99.99	1.00	2	s0.ctg000170l,s0.ctg000386l	1932700,1035400	21.1398,20.5899	20.8	Pass	Neural Network (Specific Model)	11	0.867	1932700	311.4409	2968100	0.56	2760	None	metabat2_bins.642
MAG66	97.07	1.44	10	s0.ctg000352l,s0.ctg000848l,s0.ctg000916l,s646.ctg000999l,s0.ctg001428l,s0.ctg002321l,s2441.ctg003231l,s5682.ctg006850l,s0.ctg009010l,s9133.ctg010726l	285397,680073,699567,27445,168693,342710,23366,24387,74867,20958	27.0721,35.8895,34.0164,8.55692,34.675,28.3625,12.1486,3.42493,19.6179,4.82882	20.8	Pass	Gradient Boost (General Model)	11	0.887	680073	319.7160	2347463	0.60	2176	None	bin.6_sub
MAG67	83.39	33.55	8	s0.ctg000231l,s0.ctg000516l,s0.ctg000663l,s0.ctg000962l,s0.ctg001190l,s0.ctg001726l,s0.ctg001992l,s0.ctg002118l	230507,212864,1309212,918524,189938,439698,520322,478508	34.9438,17.7397,16.3051,19.8494,15.4634,15.2059,16.3255,29.4583	20.6	Fail	Gradient Boost (General Model)	11	0.877	918524	312.7913	4299573	0.41	4025	None	metabat2_bins.426_sub
MAG68	100.00	20.34	4	s141.ctg000213l,s0.ctg000218l,s0.ctg000884l,s0.ctg001099l	1897794,1108734,534364,338733	22.1427,18.229,19.1769,20.5944	20.0	Fail	Neural Network (Specific Model)	11	0.840	1108734	317.5200	3879625	0.38	3427	None	metabat2_bins.211
MAG69	79.68	0.62	3	s0.ctg000034l,s0.ctg000783l,s0.ctg001331l	1585109,594723,614907	20.7811,19.2682,18.5839	19.5	Pass	Neural Network (Specific Model)	11	0.877	1585109	327.8742	2794739	0.48	2496	None	metabat2_bins.292_sub
MAG70	25.91	0.30	1	s0.ctg000056l	928705	19.5308	19.5	Fail	Neural Network (Specific Model)	11	0.893	928705	327.8377	928705	0.42	844	None	bin.231
MAG71	37.41	0.09	1	s18.ctg000875l	1241130	19.4787	19.4	Fail	Neural Network (Specific Model)	11	0.900	1241130	362.1592	1241130	0.46	1030	None	bin.178
MAG72	100.00	44.01	6	s4.ctg000006l,s4.ctg000194l,s4.ctg000309l,s4.ctg000369l,s4.ctg000882l,s4.ctg001212l	714514,760023,801898,297898,302604,668356	20.1305,20.6502,16.3268,19.9135,17.8718,21.494	19.3	Fail	Neural Network (Specific Model)	11	0.873	714514	348.6623	3545293	0.60	2961	None	metabat2_bins.331_sub
MAG73	100.00	0.28	1	s181.ctg000289c	1993113	18.1516	18.1	Pass	Gradient Boost (General Model)	11	0.864	1993113	343.4035	1993113	0.44	1673	None	s181.ctg000289c
MAG74	65.95	0.00	1	s0.ctg000455l	1882553	18.1431	18.1	Pass	Neural Network (Specific Model)	11	0.881	1882553	309.4885	1882553	0.57	1789	None	bin.83
MAG75	26.79	0.05	1	s4.ctg000642l	673853	17.8987	17.8	Fail	Neural Network (Specific Model)	11	0.852	673853	377.9606	673853	0.60	507	None	bin.187
MAG76	26.86	0.07	1	s0.ctg000649l	1057989	17.7022	17.7	Fail	Neural Network (Specific Model)	11	0.864	1057989	322.1055	1057989	0.42	948	None	bin.212
MAG77	80.69	11.00	5	s0.ctg000064l,s0.ctg000261l,s0.ctg000482l,s0.ctg000913l,s0.ctg001878l	417944,1381548,232828,829891,283267	28.8531,24.1968,9.26516,16.1293,9.43806	17.5	Fail	Neural Network (Specific Model)	11	0.865	829891	321.7991	3145478	0.44	2822	None	bin.62
MAG78	73.58	5.90	8	s0.ctg000412l,s269.ctg000441c,s0.ctg001244l,s1710.ctg002373l,s0.ctg002461l,s4238.ctg005267l,s4642.ctg005710l,s6619.ctg007886l	1257711,576992,650500,143178,232126,65926,48003,52603	22.6062,20.8025,19.9986,11.9962,22.6993,15.5469,12.4326,13.5583	17.4	Pass	Neural Network (Specific Model)	11	0.878	650500	306.2410	3027039	0.48	2900	None	metabat2_bins.575
MAG79	99.89	2.38	1	s304.ctg000489c	3070484	17.1979	17.1	Pass	Gradient Boost (General Model)	11	0.886	3070484	287.8153	3070484	0.30	3157	None	bin.15
MAG80	99.98	0.99	1	s147.ctg000226c	2692705	16.7227	16.7	Pass	Neural Network (Specific Model)	11	0.795	2692705	319.9065	2692705	0.51	2235	None	bin.29
MAG81	40.43	0.27	1	s0.ctg000010l	1232541	16.7532	16.7	Fail	Neural Network (Specific Model)	11	0.892	1232541	327.7304	1232541	0.37	1120	None	bin.155
MAG82	26.15	0.35	1	s0.ctg000270l	944222	16.6308	16.6	Fail	Neural Network (Specific Model)	11	0.877	944222	327.9324	944222	0.47	843	None	bin.281
MAG83	97.49	0.91	2	s19.ctg000029c,s0.ctg003820l	2134444,33608	20.0344,12.9637	16.4	Pass	Gradient Boost (General Model)	11	0.893	2134444	329.9438	2168052	0.62	1958	None	metabat2_bins.300
MAG84	45.16	8.69	2	s235.ctg000373l,s0.ctg000693l	844429,1005798	12.5225,20.2589	16.3	Fail	Neural Network (Specific Model)	11	0.858	1005798	300.5385	1850227	0.56	1764	None	bin.159
MAG85	98.07	70.92	10	s0.ctg000264l,s0.ctg000332l,s0.ctg000360l,s0.ctg000408l,s0.ctg000529l,s0.ctg000615l,s0.ctg000703l,s0.ctg001398l,s0.ctg003571l,s0.ctg004082l	742224,1400914,453070,265372,429380,263140,497550,912395,132418,148401	15.8353,15.6412,17.0597,17.3156,17.8408,15.0087,16.8091,18.1685,15.7533,12.8197	16.2	Fail	Gradient Boost (General Model)	11	0.861	742224	292.1745	5244864	0.57	5163	None	metabat2_bins.269_sub
MAG86	53.96	0.35	4	s0.ctg000469l,s0.ctg001078l,s767.ctg001170l,s0.ctg003201l	401368,560487,414705,153572	7.00898,38.9825,7.47693,11.3798	16.2	Fail	Neural Network (Specific Model)	11	0.858	414705	290.8772	1530132	0.56	1507	None	bin.160
MAG87	93.26	0.32	1	s0.ctg000168l	3350178	16.1323	16.1	Pass	Neural Network (Specific Model)	11	0.890	3350178	312.7109	3350178	0.43	3186	None	bin.44
MAG88	79.53	2.86	6	s0.ctg001523l,s0.ctg001722l,s0.ctg002163l,s0.ctg002303l,s0.ctg005648l,s0.ctg009344l	297649,563601,574925,949458,100024,39322	14.1796,18.7949,14.8214,17.8509,13.0376,17.5746	16.0	Pass	Neural Network (Specific Model)	11	0.870	574925	317.2813	2524979	0.41	2311	None	metabat2_bins.70
MAG89	99.64	1.04	1	s298.ctg000483c	2316656	15.9362	15.9	Pass	Neural Network (Specific Model)	11	0.848	2316656	319.2434	2316656	0.49	2054	None	bin.36
MAG90	89.35	0.69	3	s18.ctg000542l,s18.ctg000574l,s18.ctg001146l	910186,1944148,299927	12.8841,23.8006,11.056	15.9	Pass	Neural Network (Specific Model)	11	0.894	1944148	357.0918	3154261	0.57	2635	None	bin.60
MAG91	93.37	1.33	1	s337.ctg000535c	1285570	15.6128	15.6	Pass	Gradient Boost (General Model)	11	0.890	1285570	291.7914	1285570	0.26	1309	None	bin.43
MAG92	46.42	0.39	2	s0.ctg000058l,s0.ctg000428l	718944,661879	17.8457,13.3507	15.5	Fail	Neural Network (Specific Model)	11	0.867	718944	332.9408	1380823	0.45	1200	None	metabat2_bins.280_sub
MAG93	96.91	1.82	1	s171.ctg000272l	3399733	15.4244	15.4	Pass	Gradient Boost (General Model)	11	0.864	3399733	344.3041	3399733	0.57	2848	None	bin.32
MAG94	100.00	1.69	3	s186.ctg000296l,s408.ctg000645l,s440.ctg000688l	1131687,437742,1939327	14.8301,13.6761,17.4994	15.3	Pass	Neural Network (Specific Model)	11	0.870	1939327	339.1158	3508756	0.64	3005	None	metabat2_bins.169
MAG95	13.95	0.00	1	s0.ctg001213l	385388	15.2984	15.2	Fail	Neural Network (Specific Model)	11	0.884	385388	288.7284	385388	0.38	394	None	bin.267
MAG96	13.66	0.00	1	s0.ctg000779l	372004	15.1852	15.1	Fail	Neural Network (Specific Model)	11	0.878	372004	310.8917	372004	0.38	351	None	bin.266
MAG97	18.12	0.10	1	s0.ctg000109l	478461	15.1053	15.1	Fail	Neural Network (Specific Model)	11	0.884	478461	326.8657	478461	0.38	432	None	bin.259
MAG98	12.61	0.01	1	s0.ctg001567l	466912	15.0366	15.0	Fail	Neural Network (Specific Model)	11	0.847	466912	298.0023	466912	0.56	443	None	bin.246
MAG99	72.48	0.34	1	s16.ctg000022c	2002727	14.9361	14.9	Pass	Neural Network (Specific Model)	11	0.896	2002727	303.2447	2002727	0.40	1978	None	bin.79
MAG100	39.36	0.19	1	s0.ctg001137l	1271788	14.7522	14.7	Fail	Neural Network (Specific Model)	11	0.873	1271788	304.6426	1271788	0.42	1217	None	bin.152
MAG101	99.90	0.72	6	s18.ctg000091l,s18.ctg000560l,s18.ctg000575l,s18.ctg000738l,s18.ctg000831l,s18.ctg002078l	1403445,786521,833696,619859,346126,233047	15.6025,16.3329,14.3826,12.1086,14.3269,14.9483	14.6	Pass	Neural Network (Specific Model)	11	0.898	833696	342.7251	4222694	0.46	3696	None	metabat2_bins.336
MAG102	94.81	3.54	2	s0.ctg000112l,s0.ctg000496l	2533940,1672928	13.4696,15.726	14.5	Pass	Gradient Boost (General Model)	11	0.891	2533940	353.8609	4206868	0.42	3536	None	metabat2_bins.430
MAG103	99.98	0.23	1	s98.ctg000147c	3733713	14.4107	14.4	Pass	Neural Network (Specific Model)	11	0.894	3733713	382.2614	3733713	0.40	2915	None	bin.4
MAG104	37.03	10.57	3	s0.ctg000454l,s0.ctg000664l,s0.ctg002162l	352736,237794,1183126	12.5083,14.9282,16.0333	14.4	Fail	Neural Network (Specific Model)	11	0.863	1183126	307.6765	1773656	0.43	1663	None	metabat2_bins.443
MAG105	99.81	37.86	6	s0.ctg000320l,s0.ctg000379l,s0.ctg000620l,s0.ctg002044l,s0.ctg002213l,s0.ctg002796l	887344,1083482,692786,457674,547297,197549	13.3725,13.9437,12.191,18.7722,14.4822,13.2244	14.3	Fail	Neural Network (Specific Model)	11	0.885	887344	304.2025	3866132	0.42	3758	None	metabat2_bins.382_sub
MAG106	99.79	0.88	1	s573.ctg000888l	2479347	14.3254	14.3	Pass	Neural Network (Specific Model)	11	0.860	2479347	324.2929	2479347	0.60	2195	None	bin.40
MAG107	99.98	0.06	1	s57.ctg000080c	2407636	14.2618	14.2	Pass	Neural Network (Specific Model)	11	0.872	2407636	346.7501	2407636	0.60	2021	None	bin.39
MAG108	64.34	3.50	2	s18.ctg000228l,s329.ctg000524l	1218179,303803	18.7578,9.31159	14.0	Pass	Neural Network (Specific Model)	11	0.869	1218179	337.1046	1521982	0.54	1310	None	bin.112
MAG109	74.30	0.23	1	s116.ctg000175l	2581860	14.0163	14.0	Pass	Neural Network (Specific Model)	11	0.867	2581860	320.1036	2581860	0.45	2336	None	bin.100
MAG110	37.85	0.34	1	s0.ctg000532l	783557	13.9934	13.9	Fail	Neural Network (Specific Model)	11	0.882	783557	309.4987	783557	0.58	746	None	bin.151
MAG111	100.00	0.18	1	s223.ctg000348c	3936221	13.8692	13.8	Pass	Neural Network (Specific Model)	11	0.870	3936221	316.1296	3936221	0.42	3618	None	s223.ctg000348c
MAG112	83.08	12.12	6	s0.ctg000247l,s0.ctg000315l,s0.ctg000387l,s0.ctg000623l,s771.ctg001177l,s0.ctg001215l	1181025,510325,627230,109869,451932,557967	9.19361,12.5085,16.7185,10.8459,15.6921,18.405	13.8	Fail	Neural Network (Specific Model)	11	0.881	627230	322.1896	3438348	0.43	3139	None	bin.121
MAG113	99.72	0.20	3	s0.ctg000308l,s365.ctg000581l,s0.ctg004209l	1248926,1381920,266379	13.1225,14.3328,13.6647	13.7	Pass	Neural Network (Specific Model)	11	0.894	1248926	313.1039	2897225	0.41	2763	None	bin.24
MAG114	83.93	0.07	1	s146.ctg000225l	2478893	13.62	13.6	Pass	Neural Network (Specific Model)	11	0.891	2478893	319.6275	2478893	0.38	2306	None	bin.48
MAG115	32.39	0.05	1	s0.ctg000070l	840022	13.4822	13.4	Fail	Neural Network (Specific Model)	11	0.892	840022	324.1334	840022	0.42	772	None	bin.177
MAG116	86.07	2.60	2	s94.ctg000141l,s0.ctg001311l	2236128,1526894	12.4176,14.2308	13.3	Pass	Neural Network (Specific Model)	11	0.879	2236128	314.4122	3763022	0.46	3515	None	bin.50
MAG117	100.00	0.26	1	s38.ctg000055c	2964517	13.382	13.3	Pass	Neural Network (Specific Model)	11	0.879	2964517	354.5259	2964517	0.55	2455	None	s38.ctg000055c
MAG118	86.37	0.49	5	s0.ctg000131l,s0.ctg000240l,s0.ctg000323l,s0.ctg000327l,s0.ctg001896l	1805091,382049,270434,562995,412988	12.728,12.056,11.2003,13.3539,15.2553	12.9	Pass	Neural Network (Specific Model)	11	0.888	1805091	319.8185	3433557	0.42	3184	None	bin.63
MAG119	49.42	0.55	1	s0.ctg000026l	2083529	12.7315	12.7	Fail	Neural Network (Specific Model)	11	0.855	2083529	328.9840	2083529	0.43	1808	None	bin.128
MAG120	99.37	5.15	1	s9.ctg000013c	3255605	11.914	11.9	Pass	Neural Network (Specific Model)	11	0.896	3255605	352.2464	3255605	0.38	2764	None	bin.31
MAG121	48.20	0.52	1	s43.ctg000062l	1386421	11.5236	11.5	Fail	Neural Network (Specific Model)	11	0.837	1386421	302.9672	1386421	0.57	1279	None	bin.162
MAG122	30.96	0.20	1	s0.ctg000244l	1033584	11.5409	11.5	Fail	Neural Network (Specific Model)	11	0.867	1033584	299.3750	1033584	0.42	1000	None	bin.188
MAG123	90.02	40.95	5	s203.ctg000318l,s0.ctg000805l,s1093.ctg001608l,s0.ctg001924l,s2518.ctg003318l	1761041,660486,806754,515932,305345	12.2666,11.3195,10.4414,12.6516,10.2297	11.3	Fail	Neural Network (Specific Model)	11	0.882	806754	309.8468	4049558	0.41	3852	None	metabat2_bins.727
MAG124	44.74	0.01	1	s0.ctg000410l	1387025	11.375	11.3	Fail	Neural Network (Specific Model)	11	0.862	1387025	311.4891	1387025	0.41	1282	None	bin.119
MAG125	99.92	0.37	1	s90.ctg000134c	2751808	11.3076	11.3	Pass	Gradient Boost (General Model)	11	0.894	2751808	315.7236	2751808	0.44	2601	None	bin.11
MAG126	50.34	0.24	3	s0.ctg000604l,s630.ctg000969l,s0.ctg006134l	1258963,140820,175410	8.66582,11.8915,12.8305	11.1	Fail	Neural Network (Specific Model)	11	0.857	1258963	294.4938	1575193	0.43	1531	None	bin.140
MAG127	25.47	0.54	7	s0.ctg000873l,s0.ctg001049l,s1023.ctg001520l,s0.ctg002696l,s0.ctg005158l,s0.ctg008511l,s9483.ctg011156l	95752,518290,17857,22581,187887,22292,19899	11.1552,11.21,9.81437,11.2439,10.7926,10.1872,11.9664	10.9	Fail	Neural Network (Specific Model)	11	0.849	518290	286.8434	884558	0.42	875	None	metabat2_bins.680
MAG128	99.99	26.18	6	s0.ctg000148l,s0.ctg000390l,s0.ctg000411l,s0.ctg001053l,s0.ctg001101l,s722.ctg001104l	766432,251458,773416,951407,662261,1213766	11.1574,9.58545,10.8048,12.3379,8.46507,12.5704	10.8	Fail	Neural Network (Specific Model)	11	0.863	773416	323.6710	4618740	0.44	4112	None	metabat2_bins.365
MAG129	99.97	5.38	4	s0.ctg000012l,s0.ctg000189l,s0.ctg000239l,s1151.ctg001682l	1338863,834703,1202014,269274	11.0511,10.4277,10.5082,11.272	10.8	Pass	Neural Network (Specific Model)	11	0.867	1202014	316.0006	3644854	0.56	3340	None	bin.22
MAG130	98.93	4.41	2	s0.ctg000128l,s276.ctg000448c	3699041,1532094	11.3614,10.3254	10.8	Pass	Gradient Boost (General Model)	11	0.866	3699041	337.4835	5231135	0.46	4482	None	bin.34
MAG131	54.19	0.46	4	s18.ctg000041l,s312.ctg000501l,s422.ctg000668l,s889.ctg001347l	742677,1303215,523322,315671	9.94529,11.768,12.0903,9.20071	10.7	Fail	Neural Network (Specific Model)	11	0.891	742677	366.8734	2884885	0.42	2338	None	bin.118
MAG132	99.97	3.40	1	s0.ctg000095l	3375340	10.6293	10.6	Pass	Neural Network (Specific Model)	11	0.820	3375340	312.9512	3375340	0.38	2953	None	bin.17
MAG133	21.94	2.67	2	s340.ctg000538l,s945.ctg001424l	283426,277172	10.475,10.7286	10.6	Fail	Neural Network (Specific Model)	11	0.882	283426	359.3137	560598	0.63	459	None	bin.241
MAG134	71.39	0.46	2	s0.ctg000830l,s558.ctg000866l	1123238,1358924	10.6846,10.4597	10.5	Pass	Neural Network (Specific Model)	11	0.882	1358924	341.7373	2482162	0.44	2139	None	bin.167
MAG135	12.40	0.35	1	s0.ctg001283l	431039	10.0703	10.0	Fail	Neural Network (Specific Model)	11	0.858	431039	293.9714	431039	0.57	420	None	bin.319
MAG136	57.32	2.45	6	s151.ctg000236l,s0.ctg001254l,s1253.ctg001813l,s1930.ctg002631l,s3396.ctg004317l,s4315.ctg005347l	1018192,266093,166903,70997,176723,49531	9.48503,9.70728,7.92341,11.5833,10.2264,11.1208	10.0	Fail	Neural Network (Specific Model)	11	0.856	1018192	298.0954	1748439	0.42	1678	None	metabat2_bins.194
MAG137	97.35	3.96	4	s189.ctg000299c,s330.ctg000525l,s4655.ctg005724c,s9470.ctg011136l	1796180,633767,147272,25817	10.8986,11.17,12.0956,5.75163	9.9	Pass	Gradient Boost (General Model)	11	0.877	1796180	299.4352	2603036	0.53	2546	None	bin.33
MAG138	41.63	0.07	1	s0.ctg000278l	1581883	9.61439	9.6	Fail	Neural Network (Specific Model)	11	0.893	1581883	320.9809	1581883	0.44	1469	None	bin.120
MAG139	51.18	0.92	2	s0.ctg000146l,s0.ctg000497l	534072,869337	10.3957,8.48485	9.4	Fail	Neural Network (Specific Model)	11	0.867	869337	289.7555	1403409	0.37	1403	None	bin.133
MAG140	99.38	0.30	2	s83.ctg000124c,s471.ctg000737l	377116,1524504	10.136,8.84403	9.4	Pass	Neural Network (Specific Model)	11	0.868	1524504	343.7064	1901620	0.62	1604	None	bin.25
MAG141	97.71	0.98	1	s344.ctg000546c	1863323	9.3528	9.3	Pass	Gradient Boost (General Model)	11	0.902	1863323	330.1237	1863323	0.47	1698	None	bin.7
MAG142	98.10	22.54	10	s15.ctg000021l,s64.ctg000094l,s139.ctg000210l,s167.ctg000267l,s409.ctg000646l,s64.ctg001012l,s2363.ctg003145l,s2608.ctg003426l,s0.ctg003621l,s0.ctg004842l	216722,458148,808949,688349,300504,343189,66859,37583,308386,166969	4.639,9.57567,10.104,10.1744,11.8101,9.43411,9.22031,6.18187,14.849,6.38859	9.2	Fail	Gradient Boost (General Model)	11	0.865	458148	294.4469	3395658	0.58	3332	None	metabat2_bins.645
MAG143	100.00	7.08	1	s161.ctg000258c	1680942	9.26463	9.2	Pass	Gradient Boost (General Model)	11	0.863	1680942	270.3330	1680942	0.26	1796	None	s161.ctg000258c
MAG144	43.68	4.66	2	s18.ctg000359l,s18.ctg001088l	1444218,718484	9.77094,8.78017	9.2	Fail	Neural Network (Specific Model)	11	0.910	1444218	400.3878	2162702	0.42	1640	None	bin.108
MAG145	10.43	0.00	1	s2989.ctg003860l	390497	9.23719	9.2	Fail	Neural Network (Specific Model)	11	0.876	390497	338.9792	390497	0.47	337	None	bin.291_sub
MAG146	97.01	0.96	1	s142.ctg000214c	2667404	9.23539	9.2	Pass	Gradient Boost (General Model)	11	0.885	2667404	288.3824	2667404	0.30	2735	None	bin.28
MAG147	82.81	14.89	6	s0.ctg000407l,s702.ctg001079c,s0.ctg001256l,s0.ctg001318l,s0.ctg001395l,s6102.ctg007302l	694133,432908,1089218,220983,923868,48391	9.74521,8.44025,10.4415,10.0886,10.693,5.64294	9.1	Fail	Neural Network (Specific Model)	11	0.894	923868	308.5279	3409501	0.43	3300	None	metabat2_bins.347_sub
MAG148	43.98	0.00	4	s0.ctg000722l,s0.ctg002025l,s0.ctg003767l,s4070.ctg005079l	311464,791447,157447,90286	10.9001,10.4174,9.01263,5.94151	9.0	Fail	Neural Network (Specific Model)	11	0.867	791447	317.9244	1350644	0.41	1230	None	metabat2_bins.481_sub
MAG149	7.14	0.06	6	s18.ctg002510l,s18.ctg004151l,s3414.ctg004337l,s5078.ctg006187l,s6368.ctg007602l,s18.ctg010951l	59640,59804,31967,23289,16186,17917	17.2616,15.0673,10.1096,2.65011,4.915,4.57145	9.0	Fail	Neural Network (Specific Model)	11	0.910	59640	323.6888	208803	0.56	196	None	bin.904_sub
MAG150	98.63	2.62	3	s86.ctg000127l,s119.ctg000178l,s414.ctg000656l	622025,618955,1761565	9.46528,8.16066,8.60438	8.7	Pass	Neural Network (Specific Model)	11	0.853	1761565	327.2448	3002545	0.49	2614	None	bin.30
MAG151	69.58	10.06	4	s17.ctg000024l,s0.ctg000728l,s1562.ctg002200l,s6571.ctg007834l	1815144,293545,115671,52378	9.93267,8.37057,7.97851,8.52064	8.7	Fail	Neural Network (Specific Model)	11	0.866	1815144	297.7499	2276738	0.56	2211	None	metabat2_bins.374_sub
MAG152	100.00	0.33	3	s190.ctg000300l,s190.ctg001018l,s190.ctg001603l	671665,751478,1045745	9.24018,8.51901,8.37599	8.7	Pass	Gradient Boost (General Model)	11	0.893	751478	321.7548	2468888	0.44	2288	None	bin.23
MAG153	59.84	0.99	3	s180.ctg000288l,s427.ctg000673l,s3917.ctg004903l	658825,1041001,60387	9.39543,8.67022,8.22144	8.7	Fail	Neural Network (Specific Model)	11	0.873	1041001	300.9291	1760213	0.47	1706	None	bin.109
MAG154	98.88	34.77	16	s143.ctg000217l,s143.ctg000321l,s18.ctg000325l,s396.ctg000628l,s18.ctg000868l,s18.ctg001557l,s1156.ctg001687l,s1722.ctg002389l,s2082.ctg002818l,s3833.ctg004805l,s4091.ctg005102l,s4565.ctg005626l,s5180.ctg006302l,s6221.ctg007434l,s6623.ctg007891l,s6996.ctg008297l	585019,171238,783092,921835,428194,539775,39435,442085,161270,78882,54914,49443,26777,77887,80230,62278	9.05838,7.6641,11.006,8.29037,9.16287,8.16142,11.4285,8.89646,8.72692,6.66094,8.48148,7.55412,8.98475,5.08475,9.82306,8.99425	8.6	Fail	Neural Network (Specific Model)	11	0.882	585019	344.9852	4502354	0.58	3844	None	metabat2_bins.205_sub
MAG155	98.35	1.83	3	s0.ctg000211l,s357.ctg000569l,s0.ctg003150l	1049116,2010953,347307	8.90637,8.46832,8.46281	8.6	Pass	Gradient Boost (General Model)	11	0.876	2010953	312.2574	3407376	0.45	3194	None	bin.18
MAG156	8.85	0.09	1	s519.ctg000806l	200414	8.69281	8.6	Fail	Neural Network (Specific Model)	11	0.892	200414	292.7304	200414	0.55	204	None	bin.327
MAG157	47.51	8.37	25	s263.ctg000431l,s0.ctg001462l,s1419.ctg002021l,s1974.ctg002684l,s2302.ctg003073l,s2435.ctg003225l,s2627.ctg003448l,s3287.ctg004191l,s3297.ctg004201l,s3451.ctg004376l,s3619.ctg004559l,s4000.ctg004999l,s4245.ctg005274l,s4631.ctg005696l,s4793.ctg005870l,s4885.ctg005967l,s4945.ctg006033l,s5018.ctg006118l,s5025.ctg006126l,s5289.ctg006422l,s5597.ctg006755l,s7347.ctg008685l,s7458.ctg008809l,s7857.ctg009266l,s9073.ctg010652l	47783,76902,170438,63386,58402,167374,48452,25621,147120,88083,108823,84769,38051,31642,35449,25420,29180,40959,47488,101928,45993,44273,51548,23764,21253	6.94577,5.76272,6.01682,4.84754,23.033,5.30021,24.2103,6.01696,4.9129,3.60439,3.75535,3.55457,15.7841,3.67716,22.5028,10.0838,3.98126,2.4425,3.0921,2.99618,5.05471,3.699,5.96568,13.7313,25.4996	8.6	Fail	Neural Network (Specific Model)	11	0.863	84769	271.8557	1624101	0.49	1725	None	bin.786_sub
MAG158	61.35	15.66	6	s308.ctg000495l,s0.ctg001046l,s872.ctg001323l,s1018.ctg001514l,s0.ctg002250l,s0.ctg005386l	843401,567520,178417,288558,326540,115323	9.55334,9.32171,6.47549,8.13314,8.17323,8.34726	8.3	Fail	Neural Network (Specific Model)	11	0.887	567520	320.8161	2319759	0.41	2143	None	metabat2_bins.508
MAG159	67.73	25.06	22	s342.ctg000544l,s0.ctg000980l,s715.ctg001095l,s942.ctg001420l,s982.ctg001476l,s1221.ctg001771l,s2368.ctg003153l,s0.ctg003394l,s2696.ctg003532l,s3012.ctg003883l,s0.ctg004271l,s3441.ctg004366l,s367.ctg004651l,s3913.ctg004898l,s4973.ctg006063l,s0.ctg006933l,s5841.ctg007023l,s0.ctg007521l,s6786.ctg008073l,s0.ctg008385l,s7310.ctg008644l,s9366.ctg011010l	203492,350058,345347,435511,128256,55292,31529,131146,153495,187995,46898,152999,247503,27681,50689,62617,72756,135142,33170,26487,15943,13685	7.48701,9.18973,7.64147,9.41712,8.84027,9.07178,10.0362,8.26346,7.54802,8.95818,8.77849,8.67555,7.73244,8.19832,8.5675,9.83166,7.73151,8.62271,7.746,7.13737,8.73235,5.75486	8.3	Fail	Neural Network (Specific Model)	11	0.890	203492	311.8452	2907691	0.37	2772	None	metabat2_bins.532
MAG160	79.35	0.27	5	s134.ctg000202l,s0.ctg000223l,s0.ctg000397l,s0.ctg000879l,s3826.ctg004798l	213533,869628,994838,225150,12026	6.71687,9.06888,9.55881,7.51735,8.91748	8.3	Pass	Neural Network (Specific Model)	11	0.882	869628	306.8570	2315175	0.42	2223	None	bin.74
MAG161	14.47	0.09	2	s0.ctg002288l,s4304.ctg005336l	319121,20904	8.58437,7.9549	8.2	Fail	Neural Network (Specific Model)	11	0.851	319121	328.2755	340025	0.60	294	None	metabat2_bins.14
MAG162	87.51	0.16	3	s125.ctg000186l,s227.ctg000356l,s3366.ctg004281l	2782677,477982,166007	8.42262,7.6125,8.44795	8.1	Pass	Neural Network (Specific Model)	11	0.907	2782677	363.6083	3426666	0.46	2854	None	bin.54
MAG163	26.25	4.77	6	s13.ctg000019l,s1865.ctg002552l,s18.ctg004602l,s6963.ctg008262l,s8944.ctg010495l,s18.ctg011500l	440866,115688,92434,40134,24844,15137	7.8412,9.05991,7.73702,4.2519,12.8292,6.78615	8.0	Fail	Neural Network (Specific Model)	11	0.857	440866	311.9312	729103	0.56	669	None	metabat2_bins.371
MAG164	96.49	0.89	1	s67.ctg000100l	2992002	8.03575	8.0	Pass	Gradient Boost (General Model)	11	0.862	2992002	313.2129	2992002	0.52	2752	None	bin.13
MAG165	100.00	29.14	1	s226.ctg000354l	2332126	8.05336	8.0	Fail	Gradient Boost (General Model)	11	0.880	2332126	290.1481	2332126	0.28	2363	None	s226.ctg000354l
MAG166	48.67	8.96	12	s0.ctg000195l,s910.ctg001374l,s1755.ctg002429l,s1934.ctg002635l,s2045.ctg002773l,s2135.ctg002884l,s3551.ctg004482l,s4612.ctg005676l,s5136.ctg006248l,s7111.ctg008428l,s7239.ctg008569l,s7961.ctg009387l	610471,45809,74389,54920,89562,155692,60362,153475,65531,45628,60789,71255	22.5053,2.78887,3.28415,5.18452,4.33205,24.5255,6.99751,4.93331,5.84466,2.28592,9.11188,3.67389	7.9	Fail	Neural Network (Specific Model)	11	0.864	155692	294.6486	1487883	0.58	1457	None	bin.184
MAG167	36.77	2.10	4	s334.ctg000531l,s473.ctg000743l,s983.ctg001477l,s0.ctg006103l	737844,502178,286181,111485	8.30247,8.73733,7.88333,6.9749	7.9	Fail	Neural Network (Specific Model)	11	0.855	502178	295.8419	1637688	0.44	1581	None	metabat2_bins.525_sub
MAG168	100.00	5.40	5	s216.ctg000337l,s0.ctg001692l,s0.ctg002240l,s3236.ctg004134l,s6851.ctg008143l	1292036,484090,559613,30831,69922	14.7193,10.3021,8.80702,2.63919,2.67815	7.8	Pass	Gradient Boost (General Model)	11	0.865	1292036	304.7795	2436492	0.52	2308	None	bin.49
MAG169	57.90	0.24	2	s317.ctg000507l,s645.ctg000996l	514976,1505795	8.50079,7.10603	7.8	Fail	Neural Network (Specific Model)	11	0.802	1505795	279.9137	2020771	0.28	1934	None	metabat2_bins.3
MAG170	47.19	14.50	7	s0.ctg000221l,s469.ctg000734l,s531.ctg000825l,s762.ctg001165l,s839.ctg001279l,s998.ctg001494l,s1140.ctg001668l	176748,59984,290641,343573,208761,657474,126077	6.76662,7.86869,6.45748,9.34203,9.30535,8.34918,5.57137	7.6	Fail	Neural Network (Specific Model)	11	0.855	343573	310.8130	1863258	0.58	1711	None	bin.414
MAG171	87.70	16.88	12	s80.ctg000121l,s80.ctg000561l,s80.ctg000907l,s692.ctg001066l,s80.ctg001232l,s3433.ctg004357l,s6704.ctg007984l,s7725.ctg009120l,s8615.ctg010119l,s8755.ctg010274l,s8874.ctg010417l,s9414.ctg011071l	893018,991666,451425,479299,380665,21524,30584,24983,15084,20462,24506,25563	10.0906,9.26282,9.11227,9.71364,9.93003,9.60068,5.07633,3.47989,5.6441,3.53751,9.28055,6.69248	7.6	Fail	Neural Network (Specific Model)	11	0.874	893018	307.7685	3358779	0.43	3184	None	bin.65
MAG172	74.70	3.64	8	s55.ctg000077l,s0.ctg000349l,s1191.ctg001738l,s0.ctg003104l,s3119.ctg004007l,s4068.ctg005076l,s4094.ctg005106l,s6014.ctg007208l	2331024,550486,73423,326154,65837,53794,121065,27601	11.3818,8.86814,5.59488,7.49455,3.45997,9.84705,8.76603,5.49332	7.6	Pass	Neural Network (Specific Model)	11	0.863	2331024	310.9851	3549384	0.44	3292	None	bin.94
MAG173	83.87	12.89	10	s185.ctg000294l,s199.ctg000313l,s753.ctg001151l,s884.ctg001339l,s0.ctg003609l,s3308.ctg004215l,s0.ctg004574l,s3655.ctg004603l,s5322.ctg006456l,s6411.ctg007649l	1181746,279046,152604,541906,473811,203142,139510,147930,44799,222065	9.76983,7.83745,11.9892,7.752,9.03436,7.00547,6.12087,3.59393,6.43746,4.75985	7.4	Fail	Gradient Boost (General Model)	11	0.860	541906	301.2272	3386559	0.56	3231	None	metabat2_bins.706
MAG174	85.25	9.11	5	s0.ctg000421l,s430.ctg000676l,s730.ctg001117l,s0.ctg001571l,s0.ctg001964l	502364,358349,635082,394523,247592	6.6976,6.9326,7.49637,6.39431,9.31068	7.3	Pass	Gradient Boost (General Model)	11	0.868	502364	274.9304	2137910	0.57	2256	None	metabat2_bins.486_sub
MAG175	44.17	7.23	23	s371.ctg000592l,s822.ctg001255l,s0.ctg001326l,s1338.ctg001921l,s1682.ctg002343l,s1848.ctg002533l,s1990.ctg002703l,s2204.ctg002960l,s0.ctg004216l,s3468.ctg004395l,s3612.ctg004552l,s3656.ctg004604l,s3965.ctg004957l,s4166.ctg005188l,s4607.ctg005671l,s5482.ctg006631l,s5714.ctg006884l,s6024.ctg007218l,s6114.ctg007315l,s6540.ctg007797l,s6937.ctg008233l,s7352.ctg008691l,s7358.ctg008698l	95802,125809,102601,91344,109244,48261,78531,81931,76124,104735,68723,61284,86666,52735,54959,74323,74906,90717,62564,61083,41521,48550,44011	14.0663,6.64622,18.2996,12.0439,4.57036,12.0226,5.16304,2.66421,6.69978,5.07824,4.53043,6.25909,5.38363,5.91515,5.07628,6.31921,5.23547,5.01569,12.0435,3.08682,7.4448,5.19767,7.3761	7.2	Fail	Neural Network (Specific Model)	11	0.847	81931	302.5836	1736424	0.44	1626	None	bin.871_sub
MAG176	12.04	0.01	1	s0.ctg000342l	462981	7.29328	7.2	Fail	Neural Network (Specific Model)	11	0.834	462981	311.5531	462981	0.39	414	None	bin.278
MAG177	54.92	1.28	2	s0.ctg000893l,s0.ctg003020l	942834,356738	7.77017,6.73567	7.2	Fail	Gradient Boost (General Model)	11	0.833	942834	288.8219	1299572	0.57	1252	None	bin.202
MAG178	57.64	3.28	11	s347.ctg000551l,s725.ctg001107l,s0.ctg001519l,s0.ctg001582l,s1276.ctg001841c,s1476.ctg002094l,s0.ctg002495l,s1882.ctg002574l,s3006.ctg003877l,s0.ctg004941l,s8338.ctg009803l	64141,266386,353838,190309,192886,60321,466901,132671,181253,188771,28318	7.58888,6.82767,6.64721,8.59232,8.58895,4.9662,7.61742,5.70243,5.03014,7.85563,9.07264	7.1	Fail	Neural Network (Specific Model)	11	0.870	266386	286.5496	2125795	0.38	2158	None	bin.103
MAG179	87.28	21.65	27	s193.ctg000303l,s274.ctg000446l,s275.ctg000447l,s444.ctg000698l,s525.ctg000812l,s563.ctg000872l,s18.ctg001614l,s1292.ctg001865l,s1346.ctg001933l,s1441.ctg002049l,s18.ctg002209l,s1658.ctg002312l,s1785.ctg002460l,s1948.ctg002655l,s2018.ctg002737l,s2322.ctg003095l,s2391.ctg003176l,s2892.ctg003752l,s3455.ctg004380l,s3972.ctg004965l,s4210.ctg005236l,s4228.ctg005257l,s4549.ctg005609l,s5617.ctg006778l,s6625.ctg007894l,s7835.ctg009237l,s8557.ctg010048l	192317,74418,403833,502016,353097,213338,520633,399441,311399,218734,127348,318770,510425,102567,37635,323749,93740,146023,119425,44896,47907,260917,65046,43370,34924,50895,46670	6.22598,9.81591,8.89756,5.58978,5.09923,6.16928,5.34662,7.09465,7.00149,5.75223,9.06245,8.14788,4.66403,6.44271,10.374,7.32311,4.65513,5.80928,8.17148,5.78105,6.6464,6.70244,7.28888,6.84366,7.1833,10.2267,8.09237	7.0	Fail	Neural Network (Specific Model)	11	0.884	323749	313.8656	5563533	0.45	5239	None	metabat2_bins.8
MAG180	79.78	3.28	17	s229.ctg000358l,s401.ctg000635l,s569.ctg000883l,s1053.ctg001555l,s1789.ctg002465l,s1953.ctg002660l,s2218.ctg002978l,s0.ctg003455l,s2825.ctg003677l,s2828.ctg003682l,s0.ctg003823l,s0.ctg003974l,s3990.ctg004988l,s4953.ctg006042l,s6220.ctg007433l,s7047.ctg008355l,s7297.ctg008630l	483356,358890,85309,65110,332369,73253,121186,64693,30832,40069,85200,120277,95918,151849,52540,45715,62140	8.96723,4.13046,5.1939,8.14945,8.85639,9.011,5.56729,7.03424,3.30634,7.92971,5.45539,10.6483,3.99324,7.99907,12.5618,7.36598,4.1451	7.0	Fail	Gradient Boost (General Model)	11	0.865	332369	310.6844	2268706	0.42	2110	None	bin.216
MAG181	50.40	4.47	3	s314.ctg000503l,s0.ctg000723l,s833.ctg001270l	68322,191610,1123752	7.40839,6.34984,7.00877	6.9	Fail	Neural Network (Specific Model)	11	0.860	1123752	295.3187	1383684	0.58	1346	None	metabat2_bins.518
MAG182	81.29	0.45	4	s27.ctg000038l,s421.ctg000667l,s710.ctg001089l,s930.ctg001402l	1454417,142063,413363,753078	7.36297,7.43215,6.18218,6.97568	6.9	Pass	Gradient Boost (General Model)	11	0.853	1454417	329.6935	2762921	0.57	2388	None	metabat2_bins.99
MAG183	91.51	0.38	5	s249.ctg000399l,s486.ctg000762l,s941.ctg001419l,s1427.ctg002032l,s2849.ctg003706l	337731,509279,421028,177438,69534	7.60132,7.04721,6.18473,7.93285,5.88813	6.9	Pass	Gradient Boost (General Model)	11	0.903	421028	289.3078	1515010	0.31	1579	None	bin.47
MAG184	42.92	10.75	38	s403.ctg000639l,s679.ctg001048l,s1459.ctg002070l,s1802.ctg002482l,s1946.ctg002653l,s2101.ctg002842l,s2753.ctg003595l,s2754.ctg003596c,s3140.ctg004030l,s3701.ctg004654l,s3775.ctg004741l,s3857.ctg004832l,s4073.ctg005082l,s4090.ctg005101l,s4488.ctg005543l,s4592.ctg005655l,s4657.ctg005726l,s5064.ctg006173l,s5162.ctg006281l,s5310.ctg006443l,s5628.ctg006791l,s5744.ctg006916l,s5992.ctg007179l,s6063.ctg007260l,s6412.ctg007650l,s6838.ctg008129l,s7093.ctg008408l,s7161.ctg008483l,s7247.ctg008578l,s7499.ctg008857l,s7940.ctg009362l,s8587.ctg010086l,s8789.ctg010314l,s8848.ctg010389l,s8870.ctg010413l,s8882.ctg010426l,s9666.ctg011421l,s9785.ctg011598l	63662,10185,23258,11231,45806,34365,148411,45171,16903,58179,69400,47880,15271,18436,128658,33445,43143,14792,15637,94827,54488,41514,22077,30211,7563,22380,36176,19336,29521,38894,25168,24400,46028,11750,33688,18821,23002,29015	6.17679,10.6101,2.23927,3.92401,15.2954,4.6088,10.7769,12.2684,4.0816,2.91503,4.00461,2.88079,17.8274,12.2295,6.78451,10.8212,6.04398,6.377,1.25977,6.20359,4.78091,8.97778,2.3762,8.69352,2.66464,2.59937,8.73969,9.97644,16.4992,4.00284,3.0819,4.03559,2.45464,4.32802,4.39173,11.8606,12.7601,5.7093	6.9	Fail	Neural Network (Specific Model)	11	0.849	45806	300.3387	1452692	0.63	1373	None	bin.856
MAG185	99.13	54.22	69	s3.ctg000005l,s18.ctg000111l,s137.ctg000207l,s354.ctg000565l,s18.ctg000587l,s380.ctg000605l,s478.ctg000749l,s546.ctg000850l,s18.ctg001050l,s819.ctg001249l,s837.ctg001276l,s137.ctg001277l,s18.ctg001304l,s979.ctg001473l,s1052.ctg001554l,s1065.ctg001573l,s1112.ctg001634l,s1119.ctg001641l,s1220.ctg001770l,s1328.ctg001910l,s1528.ctg002154l,s1582.ctg002223l,s1603.ctg002247l,s137.ctg002374l,s1742.ctg002413l,s1874.ctg002563l,s1889.ctg002583l,s2030.ctg002755l,s2113.ctg002857l,s2709.ctg003545l,s2933.ctg003796l,s2980.ctg003851l,s3133.ctg004022l,s18.ctg004061l,s18.ctg004113l,s3339.ctg004252l,s3616.ctg004556l,s3710.ctg004664l,s18.ctg004682l,s3764.ctg004727l,s4086.ctg005097l,s4149.ctg005170l,s4192.ctg005217l,s4207.ctg005233l,s4299.ctg005331l,s4548.ctg005608l,s4568.ctg005629l,s4661.ctg005730l,s4795.ctg005872l,s4965.ctg006054l,s4989.ctg006082l,s5001.ctg006095l,s5015.ctg006114l,s5034.ctg006138l,s5559.ctg006713l,s5638.ctg006801l,s5869.ctg007051l,s6112.ctg007312l,s6340.ctg007567l,s6770.ctg008057l,s7153.ctg008475l,s7911.ctg009330l,s8313.ctg009776l,s8391.ctg009859l,s8627.ctg010134l,s8830.ctg010368l,s9146.ctg010746l,s9597.ctg011317l,s9749.ctg011541l	317531,1301254,392179,506849,357880,146831,391253,145366,355612,441140,339070,415411,204619,120430,82789,375937,562901,152795,286139,378458,18215,369979,134420,139295,22372,145023,87704,170081,171103,37601,63450,17225,48231,400766,313313,23308,9911,13157,152598,55203,66368,60965,18052,26684,114859,57051,51760,64442,80716,129938,63360,23013,45673,70079,39150,27440,118270,99398,27785,39021,23267,19546,25398,39384,33596,21646,17013,33973,34121	6.77497,8.79474,5.98254,8.17504,7.65616,12.2362,5.95226,5.89575,6.9195,5.88811,8.00222,7.89843,6.87652,4.32276,4.34483,5.29012,5.894,6.66452,7.11912,8.09559,6.06792,8.78205,7.01268,7.9863,7.98461,7.09793,6.03433,6.1795,5.22804,3.80585,6.02325,9.61569,6.85339,6.27515,6.62532,7.65722,7.52331,7.75167,7.47672,9.37032,7.83926,4.04798,9.94872,5.44754,5.6243,5.24128,5.65454,6.05802,7.01421,5.98102,6.14852,8.01828,10.0864,3.67783,4.8911,8.06808,4.74504,7.01877,5.28746,3.51859,7.69771,6.1689,6.94764,6.52534,6.47115,11.1633,6.77679,4.47264,7.74169	6.7	Fail	Neural Network (Specific Model)	11	0.896	357880	353.1789	11139367	0.42	9445	None	metabat2_bins.326_sub
MAG186	20.05	0.35	1	s205.ctg000322l	1001881	6.74073	6.7	Fail	Neural Network (Specific Model)	11	0.864	1001881	316.2976	1001881	0.52	914	None	bin.282
MAG187	68.06	1.00	9	s192.ctg000302l,s407.ctg000644l,s553.ctg000861l,s871.ctg001322l,s0.ctg001564l,s1774.ctg002448l,s2856.ctg003713l,s2927.ctg003790l,s8532.ctg010018l	45096,285477,697571,44381,584376,24578,56448,102228,47119	3.38286,6.53089,6.59818,10.9815,7.22988,2.0411,7.33024,7.12958,9.72814	6.7	Pass	Neural Network (Specific Model)	11	0.893	584376	300.7145	1887274	0.37	1874	None	bin.70
MAG188	94.93	0.29	3	s345.ctg000547l,s345.ctg001247l,s345.ctg002497l	1400482,552511,137422	6.78086,6.46924,6.48498	6.5	Pass	Gradient Boost (General Model)	11	0.867	1400482	340.3841	2090415	0.61	1778	None	bin.46
MAG189	50.33	7.48	24	s73.ctg000108l,s219.ctg000344l,s1263.ctg001825l,s1712.ctg002377l,s2277.ctg003044l,s2449.ctg003241l,s2498.ctg003294l,s2908.ctg003770l,s3306.ctg004212l,s3401.ctg004323l,s3416.ctg004339l,s3693.ctg004645l,s5648.ctg006813l,s5807.ctg006986l,s6185.ctg007396l,s6225.ctg007439l,s6300.ctg007523l,s0.ctg008661l,s8005.ctg009434l,s8099.ctg009537l,s8318.ctg009781l,s8645.ctg010153l,s9139.ctg010732l,s0.ctg011199l	418725,56512,157639,111182,30877,26132,102737,80616,89296,116158,28755,52454,67503,41406,43961,55770,26118,23026,43800,26100,35886,24533,26553,20594	8.31226,5.81834,5.58664,7.94117,6.90835,4.46074,6.12342,4.05816,5.56779,9.38015,5.47303,4.63353,4.43012,5.93422,6.72897,5.58731,7.66886,11.5015,2.66832,6.08401,5.0232,6.08965,8.58645,8.57479	6.3	Fail	Neural Network (Specific Model)	11	0.877	102737	307.5603	1706333	0.42	1626	None	metabat2_bins.320
MAG190	14.64	0.01	1	s481.ctg000754l	478688	6.29757	6.2	Fail	Neural Network (Specific Model)	11	0.835	478688	298.1674	478688	0.46	448	None	bin.309
MAG191	48.29	6.73	11	s391.ctg000621l,s1117.ctg001639l,s1457.ctg002066l,s0.ctg002068l,s1966.ctg002674l,s3155.ctg004045l,s3552.ctg004484l,s4673.ctg005744l,s4983.ctg006075l,s5843.ctg007025l,s8672.ctg010181l	448378,448254,40707,152648,166657,19455,30547,85180,63196,57720,13773	5.80026,8.86252,5.48569,5.11215,5.55235,4.8317,6.89114,6.20983,7.0013,6.96144,6.36167	6.2	Fail	Neural Network (Specific Model)	11	0.867	448254	301.3817	1526515	0.59	1467	None	metabat2_bins.418_sub
MAG192	56.52	0.01	9	s785.ctg001196l,s1497.ctg002121l,s1596.ctg002239l,s1714.ctg002379c,s2044.ctg002772l,s2085.ctg002824l,s2807.ctg003657l,s2973.ctg003843l,s3609.ctg004549l	158871,541857,46096,215179,518706,113906,339785,194959,25970	7.34074,5.57464,6.01922,6.97212,7.00374,4.27795,6.59972,5.65028,6.36503	6.2	Fail	Neural Network (Specific Model)	11	0.880	339785	287.6472	2155329	0.61	2205	None	bin.84
MAG193	58.70	0.75	11	s140.ctg000212l,s773.ctg001179l,s1111.ctg001633l,s1561.ctg002199l,s2247.ctg003009l,s3407.ctg004329l,s4134.ctg005151l,s6697.ctg007976l,s6806.ctg008094l,s7086.ctg008401l,s9808.ctg011642l	359624,225753,256573,119006,203570,169213,61195,57244,27383,55916,12299	6.35059,6.36141,6.40731,5.3869,5.98927,5.64526,5.7045,6.45872,4.84625,7.26152,8.52087	6.2	Fail	Neural Network (Specific Model)	11	0.882	225753	303.0093	1547776	0.38	1505	None	metabat2_bins.279_sub
MAG194	93.52	0.75	2	s210.ctg000330l,s2572.ctg003383l	1051123,319940	6.34706,5.6932	6.0	Pass	Gradient Boost (General Model)	11	0.903	1051123	289.3814	1371063	0.25	1429	None	bin.51
MAG195	90.43	2.92	3	s0.ctg001788l,s0.ctg001846l,s2279.ctg003046c	1206304,245582,240838	6.10488,6.58115,5.51564	6.0	Pass	Neural Network (Specific Model)	11	0.904	1206304	300.6976	1692724	0.37	1700	None	bin.55
MAG196	31.81	3.34	18	s204.ctg000319l,s997.ctg001493l,s1363.ctg001954l,s1574.ctg002215l,s1715.ctg002381l,s1717.ctg002383l,s2260.ctg003025l,s2935.ctg003798l,s3895.ctg004877l,s4715.ctg005789l,s4756.ctg005833l,s4972.ctg006062l,s5356.ctg006491l,s5540.ctg006693l,s6304.ctg007528l,s8185.ctg009627l,s8253.ctg009708l,s9568.ctg011280l	30181,93928,162247,76868,73114,24005,73832,41713,171415,21587,57576,55321,26744,90819,35035,29565,29252,20937	2.89321,6.01233,9.88084,3.30092,7.93945,5.0978,4.02983,3.8508,6.32972,16.5997,2.52993,6.84133,2.50139,4.24506,10.4866,3.33758,6.48227,5.14033	5.9	Fail	Neural Network (Specific Model)	11	0.850	76868	278.6301	1114139	0.45	1138	None	bin.428_sub
MAG197	84.56	24.86	11	s360.ctg000573l,s1447.ctg002055l,s1686.ctg002347l,s2457.ctg003249l,s3239.ctg004137l,s3258.ctg004160l,s3456.ctg004382l,s5800.ctg006978l,s7281.ctg008614l,s8370.ctg009836l,s9576.ctg011289l	737272,1050219,266547,164210,282680,118900,156824,30832,23749,28695,17398	6.34786,7.18783,5.40335,4.34109,6.22327,7.29353,7.76318,1.95685,3.48269,5.51585,9.75342	5.9	Fail	Gradient Boost (General Model)	11	0.886	737272	277.3120	2877326	0.30	3074	None	metabat2_bins.208_sub
MAG198	33.33	0.88	5	s567.ctg000880l,s835.ctg001273l,s966.ctg001455l,s6401.ctg007638l,s835.ctg010617l	290441,23315,427041,51257,24752	6.89688,5.91526,5.97489,4.92614,5.95378	5.9	Fail	Neural Network (Specific Model)	11	0.826	427041	298.1640	816806	0.56	756	None	metabat2_bins.202
MAG199	25.00	0.10	6	s423.ctg001996l,s2943.ctg003807l,s3429.ctg004352l,s3794.ctg004762l,s3815.ctg004787l,s4226.ctg005254l	213948,239676,46198,16540,61834,49273	5.48538,6.16351,5.25521,5.3889,5.79314,7.09914	5.8	Fail	Neural Network (Specific Model)	11	0.900	213948	311.4488	627469	0.43	606	None	metabat2_bins.26
MAG200	44.13	7.28	25	s120.ctg000179l,s1145.ctg001675l,s1183.ctg001725l,s1254.ctg001814l,s0.ctg002206l,s1963.ctg002671l,s2006.ctg002725l,s2286.ctg003054l,s2321.ctg003094l,s3243.ctg004143l,s3750.ctg004709l,s3945.ctg004935l,s4003.ctg005002l,s4011.ctg005012l,s4072.ctg005081l,s4089.ctg005100l,s4179.ctg005203l,s4863.ctg005942l,s6391.ctg007626l,s6708.ctg007989l,s6724.ctg008008l,s6973.ctg008273l,s7252.ctg008583l,s7882.ctg009299l,s9660.ctg011410l	61485,20903,38099,61114,138675,68542,63567,61687,93910,32615,110504,74205,30464,69470,181625,14703,102841,27503,44757,20287,52534,18509,42062,20505,25952	5.91659,5.29904,3.71794,3.81565,5.16157,5.48202,5.5072,4.45649,4.81811,5.68825,5.48227,4.84559,9.83496,7.65352,5.63181,2.72253,4.16344,9.68227,4.00863,3.64041,5.1853,10.0678,5.15513,7.33068,8.67844	5.7	Fail	Neural Network (Specific Model)	11	0.832	69470	276.7593	1476518	0.59	1483	None	metabat2_bins.412
MAG201	98.23	0.51	5	s63.ctg000093l,s926.ctg001397l,s1867.ctg002554l,s1873.ctg002561l,s5339.ctg006474l	644602,787476,250846,200271,38362	5.48567,5.43643,6.8992,5.53136,4.86962	5.6	Pass	Gradient Boost (General Model)	11	0.854	644602	314.1850	1921557	0.53	1746	None	bin.35
MAG202	61.61	18.81	9	s0.ctg000567l,s499.ctg000776l,s1215.ctg001764l,s1234.ctg001791l,s3465.ctg004392l,s4958.ctg006047l,s0.ctg006286l,s7740.ctg009135l,s8135.ctg009573l	932863,521662,25186,321700,203054,23602,77918,25859,22083	8.42577,6.23591,4.46086,5.26005,5.56642,5.17926,5.24842,5.73352,5.17581	5.6	Fail	Neural Network (Specific Model)	11	0.876	521662	300.0167	2153927	0.41	2101	None	metabat2_bins.540_sub
MAG203	32.36	5.59	12	s842.ctg001282l,s980.ctg001474l,s1009.ctg001505l,s1045.ctg001547l,s1433.ctg002039l,s2885.ctg003744l,s3437.ctg004362l,s4231.ctg005260l,s4698.ctg005770l,s5624.ctg006787l,s7862.ctg009272l,s8561.ctg010053l	178831,40124,42121,164560,69246,87058,236794,34146,140541,32566,43232,31812	5.50586,7.50523,4.4977,4.89762,4.22997,7.20478,5.47172,5.53109,5.46464,3.95046,6.28664,6.8916	5.6	Fail	Neural Network (Specific Model)	11	0.836	164560	284.7083	1101031	0.59	1080	None	bin.210
MAG204	75.21	0.67	9	s420.ctg000665l,s575.ctg000890l,s931.ctg001403l,s0.ctg001535l,s1134.ctg001660l,s1417.ctg002019l,s1687.ctg002348l,s3026.ctg003899l,s4346.ctg005380l	889300,450039,584008,258999,160607,290895,98869,229964,52211	7.74518,4.85556,6.49766,7.95486,5.78015,3.99773,5.22885,5.30734,3.40645	5.6	Pass	Neural Network (Specific Model)	11	0.839	450039	307.7307	3014892	0.41	2744	None	bin.73
MAG205	61.76	23.98	41	s400.ctg000632l,s698.ctg001074l,s1192.ctg001739l,s1235.ctg001792l,s1410.ctg002011l,s1732.ctg002401l,s1834.ctg002519l,s1893.ctg002588l,s2087.ctg002826l,s2177.ctg002929l,s2515.ctg003315l,s2637.ctg003460l,s2777.ctg003622l,s2890.ctg003750l,s2992.ctg003863l,s3079.ctg003960l,s3249.ctg004149l,s3476.ctg004403l,s3546.ctg004476l,s3593.ctg004532l,s3704.ctg004657l,s3832.ctg004804l,s3876.ctg004854l,s3982.ctg004978l,s4230.ctg005259l,s4265.ctg005294l,s4789.ctg005866l,s5196.ctg006321l,s5610.ctg006770l,s5681.ctg006849l,s6078.ctg007275l,s4.ctg007580l,s4.ctg007582l,s6902.ctg008197l,s7223.ctg008552l,s7430.ctg008779l,s8236.ctg009688l,s8751.ctg010269l,s4.ctg010577l,s9423.ctg011081l,s4.ctg011614l	93407,81773,63312,37667,131250,102965,50679,123514,47197,69028,51362,110129,95455,36919,66205,39891,86430,29898,87819,38125,114857,28802,66132,167622,46646,28742,23804,22323,112985,29062,54734,23702,18695,54827,49057,64904,27150,63819,18011,11234,18406	3.34994,4.75027,5.66212,2.2666,6.36377,8.38525,3.45566,4.21387,3.98997,2.97279,3.88764,5.06246,7.32592,12.8867,6.57195,2.35656,3.47975,4.61325,3.04314,2.75679,5.34537,7.15046,6.78259,4.09625,4.31246,18.169,6.65443,5.77748,3.71236,4.4679,4.49846,4.81632,7.06088,3.92662,3.75492,2.50893,4.21781,5.59048,9.08885,10.7352,7.11771	5.5	Fail	Neural Network (Specific Model)	11	0.844	81773	301.8440	2488539	0.60	2327	None	bin.852
MAG206	59.48	1.50	5	s148.ctg000229l,s470.ctg000735l,s1075.ctg001584l,s2773.ctg003617l,s3765.ctg004728l	1098764,35190,584351,164108,19745	6.20061,5.82055,6.77105,6.09509,2.91687	5.5	Fail	Neural Network (Specific Model)	11	0.891	1098764	343.2753	1902158	0.51	1649	None	bin.126
MAG207	11.36	0.08	8	s118.ctg000177l,s1372.ctg002822l,s2215.ctg002975l,s3144.ctg004034l,s0.ctg006262l,s1372.ctg008672l,s1372.ctg011147l,s9659.ctg011409l	156163,28752,28480,24534,37832,32863,18468,25776	4.69009,6.13607,4.85867,3.97289,6.15721,7.87311,5.51119,5.32561	5.5	Fail	Neural Network (Specific Model)	11	0.772	37832	278.8313	352868	0.60	326	None	metabat2_bins.301
MAG208	47.24	0.12	2	s1344.ctg001928l,s2119.ctg002866l	468829,147797	5.50741,5.66822	5.5	Fail	Gradient Boost (General Model)	11	0.857	468829	292.7828	616626	0.27	603	None	bin.161
MAG209	76.73	27.76	13	s255.ctg000417l,s325.ctg000519l,s0.ctg001009l,s1015.ctg001511l,s1395.ctg001990l,s2327.ctg003101l,s2395.ctg003181l,s2552.ctg003358l,s2583.ctg003398l,s2824.ctg003676l,s0.ctg003730l,s5380.ctg006515l,s5966.ctg007153l	173238,469412,1079397,53684,243439,128629,41758,109888,136591,26984,227551,82668,31769	4.86871,5.43479,5.94656,4.18267,4.1834,6.16927,6.13144,6.15789,7.38541,3.65521,5.97737,4.60187,6.21395	5.4	Fail	Neural Network (Specific Model)	11	0.866	469412	298.9259	2805008	0.45	2713	None	metabat2_bins.445_sub
MAG210	24.92	0.04	9	s743.ctg001135l,s1943.ctg002646l,s2311.ctg003083l,s3034.ctg003908l,s4340.ctg005374l,s4788.ctg005865l,s5147.ctg006259l,s6667.ctg007942l,s7391.ctg008732l	48117,88114,109534,151259,144098,108892,56244,77144,35688	5.9647,4.74624,7.43031,4.38984,5.03346,6.32753,7.28909,4.62497,3.64306	5.4	Fail	Neural Network (Specific Model)	11	0.833	108892	283.8483	819090	0.37	804	None	bin.143
MAG211	58.92	10.44	16	s399.ctg000631l,s402.ctg000637l,s664.ctg001029l,s696.ctg001071l,s744.ctg001136l,s896.ctg001358l,s1158.ctg001689l,s1886.ctg002580l,s2127.ctg002874l,s2299.ctg003069l,s2712.ctg003548l,s3348.ctg004261l,s3783.ctg004749l,s4067.ctg005075l,s5772.ctg006948l,s8183.ctg009625l	56942,99720,68404,75777,142354,432724,71621,151272,330556,55478,266033,37306,126938,70452,95218,31974	5.81799,5.81748,4.0746,4.56952,4.72748,7.35336,5.48771,7.23019,4.71183,6.33014,4.23829,5.33798,5.95275,9.55102,3.17237,1.74761	5.3	Fail	Neural Network (Specific Model)	11	0.850	151272	264.9347	2112769	0.41	2268	None	bin.496
MAG212	32.92	0.43	3	s477.ctg000748l,s598.ctg000926l,s6707.ctg007987l	844521,220111,30704	6.97276,5.99367,3.04929	5.3	Fail	Neural Network (Specific Model)	11	0.879	844521	304.1902	1095336	0.42	1057	None	metabat2_bins.261_sub
MAG213	74.99	35.66	47	s10.ctg000015l,s91.ctg000136l,s0.ctg001285l,s935.ctg001408l,s1259.ctg001819l,s1664.ctg002319l,s2003.ctg002718l,s2027.ctg002750l,s367.ctg002752l,s2062.ctg002791l,s2064.ctg002793l,s2068.ctg002799l,s2241.ctg003003l,s2338.ctg003114l,s2480.ctg003272l,s2840.ctg003696l,s3071.ctg003951l,s3246.ctg004146l,s3314.ctg004222l,s3921.ctg004907l,s0.ctg004958l,s0.ctg004987l,s4083.ctg005092l,s4473.ctg005525l,s4507.ctg005565l,s4791.ctg005868l,s5275.ctg006408l,s5883.ctg007065l,s6307.ctg007532l,s6366.ctg007600l,s6417.ctg007658l,s0.ctg007765l,s7005.ctg008308l,s7230.ctg008560l,s7658.ctg009042l,s8092.ctg009529l,s8206.ctg009652l,s8228.ctg009678l,s8411.ctg009883l,s8536.ctg010023l,s8673.ctg010182l,s8832.ctg010370l,s9123.ctg010713l,s0.ctg011011l,s0.ctg011058l,s9713.ctg011485l,s0.ctg011525l	74714,395617,152425,218623,17217,113612,49662,85831,136862,114806,28344,59773,75554,38259,167098,44280,157474,129516,79818,12484,117646,23309,21762,31291,32410,40834,62681,51530,54140,20167,29998,16789,85723,44984,54672,30997,47133,34814,21977,48841,55212,21781,27393,20386,26872,31433,16713	5.58441,7.40634,6.72569,6.64111,4.3907,4.93671,4.38657,5.39728,5.12206,4.9757,4.35078,7.49392,6.95978,5.11011,6.16564,4.15434,6.51998,6.07837,4.36867,5.58075,5.65425,7.71113,7.71345,4.40631,4.71178,8.29085,4.86471,5.59879,5.19985,4.73178,4.6778,3.81153,4.66742,6.06928,5.26554,3.43074,3.58042,5.72479,3.65717,4.59625,4.57375,3.75262,5.09492,4.12819,4.748,5.6617,5.71793	5.3	Fail	Neural Network (Specific Model)	11	0.864	113612	278.8737	3223457	0.37	3341	None	metabat2_bins.354_sub
MAG214	88.78	3.45	10	s0.ctg000276l,s230.ctg000363l,s387.ctg000614l,s550.ctg000858l,s64.ctg000964l,s1006.ctg001502l,s1238.ctg001795l,s1503.ctg002128l,s3405.ctg004327l,s3762.ctg004724l	205619,49613,142715,300620,441861,608750,157784,460479,155900,173022	4.47408,5.43323,5.71919,5.48313,5.42915,5.70793,4.43447,6.11738,4.54378,5.72129	5.3	Pass	Gradient Boost (General Model)	11	0.882	441861	292.4529	2696363	0.58	2718	None	bin.53
MAG215	78.51	1.01	6	s114.ctg000173l,s372.ctg000594l,s593.ctg000921l,s3056.ctg003932l,s3291.ctg004195l,s9418.ctg011075l	972595,401014,379080,309335,117798,23678	6.8282,6.01864,6.22621,4.94146,4.24902,3.20903	5.2	Pass	Neural Network (Specific Model)	11	0.879	401014	324.7636	2203500	0.44	1992	None	bin.86
MAG216	88.95	0.26	7	s61.ctg000086l,s504.ctg000785l,s656.ctg001015l,s1339.ctg001922l,s2335.ctg003110l,s3800.ctg004769l,s6080.ctg007277l	2406389,682005,269717,210610,61407,117494,11257	6.7263,5.46459,5.45091,5.98671,6.72524,4.63093,1.90294	5.2	Pass	Neural Network (Specific Model)	11	0.906	2406389	364.4492	3758879	0.44	3119	None	bin.41
MAG217	58.19	9.88	26	s0.ctg000559l,s0.ctg000817l,s562.ctg000871l,s665.ctg001030l,s737.ctg001125l,s1580.ctg002221l,s2071.ctg002803l,s2211.ctg002969l,s2412.ctg003198l,s2774.ctg003618l,s2922.ctg003785l,s2956.ctg003821l,s3381.ctg004298l,s3505.ctg004434l,s3960.ctg004952l,s0.ctg005215l,s0.ctg005616l,s5141.ctg006253l,s5314.ctg006447l,s5585.ctg006743l,s5998.ctg007189l,s6030.ctg007226l,s7091.ctg008406l,s8158.ctg009598l,s8847.ctg010388l,s9070.ctg010649l	173488,109812,18086,29377,63848,105885,116743,47337,83576,177651,188315,48503,57943,37705,177087,79217,75530,74664,37942,100171,37826,39928,37323,40983,63955,24419	8.19055,5.92146,4.85404,2.8655,6.23015,2.80247,3.92965,9.45669,3.76573,7.08313,6.89134,3.91093,4.46805,3.26204,7.58416,7.21836,6.53266,3.81204,2.91945,3.04109,4.61012,5.86679,4.5872,5.05106,5.77621,2.3572	5.1	Fail	Neural Network (Specific Model)	11	0.847	105885	279.4475	2047314	0.43	2076	None	bin.853
MAG218	57.33	14.28	34	s0.ctg000752l,s520.ctg000807l,s879.ctg001334l,s897.ctg001359l,s1633.ctg002281l,s1711.ctg002376l,s1750.ctg002423l,s2102.ctg002843l,s2287.ctg003056l,s2524.ctg003325l,s2675.ctg003506l,s2692.ctg003527l,s2714.ctg003550l,s3124.ctg004013l,s3153.ctg004043l,s3918.ctg004904l,s4159.ctg005180l,s4193.ctg005218l,s4380.ctg005419l,s4857.ctg005936l,s4867.ctg005946l,s4910.ctg005993l,s4918.ctg006001l,s4942.ctg006030l,s5223.ctg006350l,s5640.ctg006803l,s6290.ctg007511l,s6311.ctg007536l,s7470.ctg008822l,s8160.ctg009601l,s8687.ctg010196l,s8730.ctg010244l,s8777.ctg010300l,s9241.ctg010857l	332835,54824,70202,32625,103704,68808,48856,66740,19667,41696,31397,22088,11664,39472,51630,143372,30470,60760,74334,31503,128924,138991,43847,48663,36452,29319,32185,44920,47720,37101,30632,31939,27054,47762	8.49631,2.9232,4.52752,7.15677,5.43539,5.3031,5.81585,5.2493,4.45945,3.19001,5.59734,4.62672,6.07139,3.84734,3.32999,5.92914,5.54601,4.40652,5.09921,4.18046,9.09891,6.15025,5.00435,3.65457,2.95628,4.13528,7.943,4.24863,4.50544,3.46943,2.31773,6.51279,3.91031,5.07017	5.0	Fail	Gradient Boost (General Model)	11	0.867	68808	291.9239	2062156	0.48	2050	None	bin.855
MAG219	96.81	0.16	9	s674.ctg001041l,s707.ctg001084l,s747.ctg001143l,s826.ctg001263l,s943.ctg001422l,s959.ctg001446l,s1977.ctg002688l,s2059.ctg002787l,s2168.ctg002920l	367115,996564,287179,303477,336361,113571,206153,168136,330528	5.29392,5.85079,5.80474,4.93519,5.67952,4.252,4.73096,4.53006,4.62217	5.0	Pass	Neural Network (Specific Model)	11	0.864	336361	331.5771	3109084	0.58	2705	None	bin.57
MAG220	77.66	4.76	12	s498.ctg000775l,s1001.ctg001497l,s498.ctg001710l,s498.ctg001715l,s498.ctg002093l,s1595.ctg002238l,s1619.ctg002265l,s2051.ctg002779l,s3402.ctg004324l,s4428.ctg005474l,s4523.ctg005581l,s7384.ctg008725l	371900,74062,425307,214464,397215,223541,23900,242325,52444,64306,77992,61394	5.3962,4.52246,5.48523,5.67963,6.40361,5.29006,3.36446,5.32725,4.52694,5.57331,4.65164,2.86719	4.9	Fail	Gradient Boost (General Model)	11	0.867	371900	287.8730	2228850	0.55	2244	None	bin.77
MAG221	27.73	7.19	22	s1314.ctg001894l,s0.ctg002085l,s367.ctg003319l,s2603.ctg003421l,s2928.ctg003791l,s3063.ctg003940l,s3327.ctg004239l,s3671.ctg004620l,s4300.ctg005332l,s4525.ctg005583l,s5201.ctg006327l,s0.ctg006520l,s5424.ctg006564l,s5570.ctg006725l,s0.ctg006759l,s6662.ctg007937l,s0.ctg008906l,s8764.ctg010284l,s0.ctg010853l,s0.ctg011451l,s0.ctg011481l,s9734.ctg011513l	71870,30857,22970,33596,80580,52735,41331,43706,27156,50043,30501,22858,54502,32639,29612,70153,35953,27572,27055,22544,18562,26156	12.1586,12.0871,4.54982,4.3659,3.16641,3.00688,3.4319,3.34457,2.63486,3.07696,2.03492,5.77268,2.46381,3.08594,3.37055,4.44155,13.3468,4.46291,5.83802,4.02389,5.72681,2.0138	4.9	Fail	Neural Network (Specific Model)	11	0.854	41331	265.3406	852951	0.37	919	None	bin.935_sub
MAG222	33.14	0.09	7	s544.ctg000845l,s1155.ctg001686l,s2688.ctg003522l,s4626.ctg005691l,s4728.ctg005802l,s4881.ctg005963l,s6769.ctg008056l	104172,574138,16037,35974,51809,130378,72463	5.54373,5.04693,3.32486,3.9502,5.51617,4.97537,6.12501	4.9	Fail	Neural Network (Specific Model)	11	0.825	574138	310.8099	984971	0.38	873	None	metabat2_bins.543
MAG223	27.61	2.79	16	s454.ctg000709l,s885.ctg001340l,s964.ctg001451l,s1199.ctg001747l,s1273.ctg001838l,s2845.ctg003702l,s4275.ctg005304l,s4369.ctg005406l,s4729.ctg005803l,s6234.ctg007449l,s6291.ctg007512l,s6655.ctg007928l,s7401.ctg008744l,s7409.ctg008753l,s8176.ctg009618l,s9632.ctg011368l	174829,113205,38149,42684,57613,36135,53634,62618,38133,37348,29865,36875,24450,39660,30960,28094	6.37843,7.74685,4.8345,3.3741,2.22428,2.63768,3.45204,4.97535,3.73217,5.13713,8.59912,3.3112,9.05741,5.67155,2.16167,2.38982	4.7	Fail	Neural Network (Specific Model)	11	0.886	53634	275.0022	844252	0.41	910	None	bin.352
MAG224	26.07	4.00	8	s1746.ctg002418l,s2895.ctg003755l,s3002.ctg003873l,s3076.ctg003956l,s3792.ctg004758l,s3888.ctg004868l,s4506.ctg005564l,s6740.ctg008024l	168758,132996,90977,103587,52361,90659,56266,155715	7.14691,3.97605,4.39367,5.70601,3.91852,4.04845,2.54227,6.47161	4.7	Fail	Neural Network (Specific Model)	11	0.831	132996	241.3788	851319	0.57	982	None	bin.860
MAG225	12.33	0.07	3	s426.ctg000672l,s3582.ctg004521l,s4625.ctg005690l	145308,170207,39069	5.85287,4.81521,3.6224	4.7	Fail	Neural Network (Specific Model)	11	0.854	145308	263.6354	354584	0.60	384	None	bin.265
MAG226	46.26	0.84	6	s290.ctg000472l,s749.ctg001147l,s820.ctg001251l,s1602.ctg002246l,s1780.ctg002454l,s3779.ctg004745l	227856,340977,260378,283675,56738,240939	4.76608,5.46334,5.23051,4.5138,3.51721,4.72623	4.7	Fail	Neural Network (Specific Model)	11	0.798	260378	314.8008	1410563	0.38	1195	None	bin.138
MAG227	94.54	8.63	26	s287.ctg000467l,s299.ctg000484l,s311.ctg000500l,s322.ctg000514l,s706.ctg001083l,s796.ctg001209l,s953.ctg001435l,s1097.ctg001616l,s1472.ctg002089l,s1847.ctg002532l,s2497.ctg003293l,s2690.ctg003525l,s2938.ctg003801c,s3413.ctg004336l,s3494.ctg004422l,s3761.ctg004723l,s4622.ctg005687l,s6275.ctg007496l,s6936.ctg008232l,s7561.ctg008928l,s8268.ctg009725l,s8333.ctg009798l,s8674.ctg010183l,s8760.ctg010280l,s9532.ctg011231l,s9606.ctg011329l	344800,261016,273011,659699,631346,300801,763867,45014,107447,45514,268024,36147,207431,31519,55406,47109,53302,39187,50815,18125,21762,24391,23132,19457,27507,24279	9.45294,5.29005,5.67355,6.10535,7.69207,6.03095,8.23734,2.45103,5.11506,6.832,6.32861,3.41565,7.52044,2.14435,5.72072,5.39162,2.13422,3.55217,9.03762,2.47054,1.94119,1.87179,1.74711,1.69312,1.4393,1.94563	4.6	Fail	Gradient Boost (General Model)	11	0.821	344800	304.8708	4380108	0.60	3941	None	bin.58
MAG228	63.64	4.90	23	s123.ctg000182l,s273.ctg000445l,s538.ctg000837l,s859.ctg001305l,s1578.ctg002219l,s2638.ctg003461l,s2812.ctg003662l,s4203.ctg005229l,s4302.ctg005334l,s4417.ctg005462l,s5332.ctg006467l,s5578.ctg006734l,s5704.ctg006874l,s5987.ctg007174l,s6026.ctg007220l,s6802.ctg008090l,s6850.ctg008141l,s7325.ctg008660l,s7785.ctg009183l,s8341.ctg009806l,s8478.ctg009958l,s9477.ctg011148l,s9512.ctg011203l	232724,48420,365509,334370,80935,191229,27724,85386,186929,72761,20401,48057,48001,52124,94164,29148,39137,43752,28050,36813,41915,20893,42308	5.88931,6.2792,4.94188,5.50751,4.89249,4.55736,2.73461,4.57243,5.31856,4.41056,3.77068,3.88202,3.691,4.74941,4.18787,4.75757,4.34955,6.85306,3.77943,3.58266,4.83774,3.69021,3.45621	4.5	Fail	Neural Network (Specific Model)	11	0.876	191229	273.4310	2170750	0.38	2325	None	metabat2_bins.454
MAG229	17.24	1.71	5	s14.ctg000020l,s465.ctg000730l,s999.ctg001495l,s1290.ctg001861l,s9212.ctg010820l	213650,66062,214277,167010,68188	5.44398,4.25504,5.5493,3.46491,3.78972	4.5	Fail	Neural Network (Specific Model)	11	0.829	213650	289.0186	729187	0.58	700	None	bin.157_sub
MAG230	75.03	2.33	8	s8.ctg000011l,s108.ctg000162l,s699.ctg001075l,s1597.ctg002241l,s2889.ctg003749l,s2977.ctg003847l,s4397.ctg005440l,s5703.ctg006873l	16204,810768,526213,88003,108903,111005,147445,148541	3.67217,6.61783,6.21956,3.69501,4.33326,4.2801,3.86048,3.85647	4.5	Pass	Neural Network (Specific Model)	11	0.855	526213	304.3803	1957082	0.45	1838	None	bin.75
MAG231	32.05	11.70	9	s1677.ctg002334l,s1691.ctg002353l,s1756.ctg002430l,s0.ctg002770l,s2366.ctg003151l,s5045.ctg006150l,s5753.ctg006925l,s5940.ctg007124l,s8020.ctg009450l	57179,322520,203311,247264,161481,24343,98549,41363,17978	3.63501,5.51174,7.07619,5.11553,5.91185,2.3463,4.71337,2.5253,2.83902	4.4	Fail	Neural Network (Specific Model)	11	0.862	203311	314.8296	1173988	0.43	1074	None	bin.276
MAG232	25.85	2.82	14	s769.ctg001173l,s801.ctg001223l,s803.ctg001227l,s1858.ctg002545l,s1957.ctg002665l,s2545.ctg003351l,s2858.ctg003715l,s3008.ctg003879l,s3052.ctg003928l,s3570.ctg004506l,s4281.ctg005310l,s4502.ctg005560l,s6568.ctg007830l,s6727.ctg008011l	177603,61386,165590,56977,144681,129215,103187,50893,31518,138425,137716,61369,33928,50368	4.57198,6.70099,4.77406,5.57362,4.19338,3.80213,4.84768,3.52372,5.1374,4.27528,4.35465,4.06001,2.32746,3.00494	4.3	Fail	Neural Network (Specific Model)	11	0.899	137716	332.1226	1342856	0.46	1215	None	bin.761_sub
MAG233	22.77	2.64	20	s888.ctg001345l,s1066.ctg001574l,s1532.ctg002160l,s1623.ctg002270l,s1724.ctg002391l,s1872.ctg002560l,s2080.ctg002815l,s2588.ctg003404l,s3035.ctg003909l,s3058.ctg003935l,s3097.ctg003979l,s3166.ctg004060l,s3185.ctg004080l,s3674.ctg004623l,s4483.ctg005536l,s4491.ctg005548l,s5575.ctg006731l,s7316.ctg008650l,s8998.ctg010560l,s9253.ctg010871l	61372,229916,38761,35949,23711,78860,116104,22999,44858,134133,82403,33618,70697,118006,18486,41589,26337,30924,39225,36244	3.62032,4.34217,3.23457,5.32657,3.96571,3.56464,5.35104,3.31984,3.45831,5.48067,4.83751,1.96665,3.39904,3.78065,4.75578,4.54741,5.02024,6.98872,2.98928,3.57658	4.1	Fail	Neural Network (Specific Model)	11	0.894	82403	318.9169	1284192	0.44	1203	None	metabat2_bins.110_sub
MAG234	86.37	3.45	8	s398.ctg000630l,s524.ctg000811l,s1202.ctg001751l,s1320.ctg001901l,s3328.ctg004240l,s4119.ctg005134l,s4531.ctg005590l,s5291.ctg006424l	100459,780463,117525,77858,139406,70919,32110,45386	3.89091,5.37142,4.10648,3.82744,4.8459,3.79905,3.52572,3.82748	4.1	Pass	Gradient Boost (General Model)	11	0.846	780463	275.8212	1364126	0.30	1398	None	metabat2_bins.551
MAG235	81.18	4.17	11	s485.ctg000760l,s618.ctg000952l,s1264.ctg001826l,s1325.ctg001907l,s2038.ctg002765l,s2176.ctg002928l,s2986.ctg003857l,s3149.ctg004039l,s3911.ctg004895l,s5614.ctg006775l,s6424.ctg007665l	464965,269932,79471,107284,296448,80261,54043,249326,43013,72036,160407	4.42987,3.76375,4.10981,5.03667,4.23172,3.7565,2.66114,4.86487,3.51989,5.58006,3.94584	4.1	Fail	Neural Network (Specific Model)	11	0.857	269932	293.2803	1877186	0.50	1834	None	bin.64
MAG236	24.11	3.71	14	s262.ctg000430l,s448.ctg000702l,s2024.ctg002747l,s3992.ctg004990l,s4216.ctg005242l,s4391.ctg005433l,s4641.ctg005709l,s6161.ctg007368l,s6523.ctg007774c,s6998.ctg008300l,s7602.ctg008973l,s7955.ctg009379l,s8269.ctg009726l,s8634.ctg010141l	33209,245108,31807,56094,26057,39369,53192,25250,17154,52047,42992,28194,43835,20006	3.43232,4.59402,4.94131,3.83621,2.59104,2.735,4.62873,2.52602,12.1917,2.23838,2.41224,1.95093,8.90761,1.26113	4.1	Fail	Neural Network (Specific Model)	11	0.872	52047	286.4594	714314	0.42	727	None	bin.580
MAG237	85.46	0.63	7	s576.ctg000891l,s1416.ctg002017l,s1423.ctg002027l,s2005.ctg002723l,s2125.ctg002872l,s2130.ctg002878l,s2730.ctg003567l	98468,529904,398830,49907,332643,338622,428681	4.49775,4.0272,3.81779,3.85861,4.49721,4.05153,4.051	4.1	Pass	Gradient Boost (General Model)	11	0.835	398830	265.1260	2177055	0.61	2294	None	bin.71
MAG238	72.97	6.78	25	s224.ctg000350l,s270.ctg000442l,s858.ctg001303l,s994.ctg001490l,s1072.ctg001580l,s1979.ctg002690l,s2170.ctg002922l,s2750.ctg003592l,s2911.ctg003773l,s3563.ctg004498l,s3784.ctg004750l,s3878.ctg004856l,s4294.ctg005325l,s4936.ctg006024l,s5991.ctg007178l,s6174.ctg007382l,s6505.ctg007751l,s6814.ctg008102l,s7860.ctg009270l,s7928.ctg009349l,s8441.ctg009915l,s8558.ctg010049l,s9222.ctg010833l,s9393.ctg011043l,s9788.ctg011605l	212685,53944,265971,49150,45916,58751,234922,190992,321666,38100,100956,124416,38339,107319,39637,61235,65004,87459,31848,68499,32687,38570,23124,25972,16726	4.58432,2.09986,4.0311,2.35245,4.07442,1.9628,5.68068,6.19184,4.56039,3.92321,3.33277,5.01539,6.61201,3.66084,4.39426,1.97079,4.52029,3.24235,1.54003,6.46182,3.89332,2.44552,4.5118,2.24421,7.02908	4.0	Fail	Gradient Boost (General Model)	11	0.852	190992	248.2950	2333888	0.32	2681	None	bin.82
MAG239	64.30	0.00	15	s257.ctg000420l,s353.ctg000564l,s0.ctg000914l,s1404.ctg002003l,s1718.ctg002384l,s2300.ctg003071l,s2430.ctg003219l,s2769.ctg003613l,s2842.ctg003698l,s4288.ctg005317l,s5733.ctg006904l,s7699.ctg009090l,s7954.ctg009378l,s8365.ctg009831l,s9529.ctg011224l	42331,136956,708835,101713,278364,173768,199589,246412,24757,41663,64856,58896,71611,40628,31850	4.68559,3.80083,5.24264,3.48612,3.97042,4.82493,4.46419,4.83959,3.64108,3.99533,4.0329,4.17482,3.14024,3.07631,2.65833	4.0	Fail	Neural Network (Specific Model)	11	0.890	246412	295.9637	2222229	0.41	2234	None	bin.81
MAG240	16.32	0.12	5	s1299.ctg001874l,s1675.ctg002332l,s3572.ctg004508l,s3937.ctg004926l,s6173.ctg007381l	88074,102158,112405,74537,97962	2.69057,5.50572,3.96308,4.29875,3.31476	3.9	Fail	Neural Network (Specific Model)	11	0.831	97962	240.5273	475136	0.59	550	None	bin.250_sub
MAG241	28.16	5.90	15	s934.ctg001406l,s1168.ctg001702l,s2417.ctg003204l,s2424.ctg003212l,s2602.ctg003420l,s2953.ctg003817l,s3908.ctg004891l,s4801.ctg005878l,s5904.ctg007086l,s6183.ctg007394l,s6718.ctg008000l,s6853.ctg008145l,s6889.ctg008184l,s7631.ctg009011l,s8145.ctg009584l	30548,35654,84210,35172,101737,54334,33652,43183,65393,28857,61174,79511,33070,32764,68012	2.39042,4.28695,4.65928,4.85107,4.85651,3.94624,4.63295,5.04645,3.61107,2.53517,4.36976,2.55675,3.21157,3.8451,4.06353	3.9	Fail	Neural Network (Specific Model)	11	0.832	65393	264.1133	787271	0.56	830	None	bin.419
MAG242	52.96	1.91	5	s74.ctg000110l,s1321.ctg001902l,s1353.ctg001940l,s2053.ctg002781l,s5293.ctg006426l	81506,397563,97505,205519,55767	3.19648,4.42268,3.15441,4.1863,4.46477	3.8	Fail	Gradient Boost (General Model)	11	0.874	205519	259.6819	837860	0.27	943	None	metabat2_bins.355
MAG243	76.57	0.07	8	s1184.ctg001727l,s1198.ctg001746l,s1752.ctg002425l,s3238.ctg004136l,s3717.ctg004671l,s3789.ctg004755l,s6178.ctg007389l,s6245.ctg007460l	109157,320308,183423,49229,102616,39268,45349,88078	4.38701,4.14443,4.99903,3.16041,4.1842,2.96684,3.26547,3.51913	3.8	Pass	Gradient Boost (General Model)	11	0.875	183423	256.3720	937428	0.28	1070	None	bin.88
MAG244	59.22	11.85	23	s1.ctg000002l,s87.ctg000129l,s554.ctg000862l,s1091.ctg001605l,s1392.ctg001987l,s1667.ctg002323l,s1870.ctg002558l,s2647.ctg003473l,s3560.ctg004495l,s3720.ctg004674l,s4285.ctg005314l,s4392.ctg005434l,s4940.ctg006028l,s5426.ctg006567l,s5539.ctg006692l,s5661.ctg006828l,s7886.ctg009303l,s8090.ctg009527l,s8570.ctg010064l,s8618.ctg010123l,s8927.ctg010478l,s9046.ctg010622l,s9419.ctg011076l	171597,175840,113272,174774,68791,22161,70001,104314,99712,92865,167380,53261,50291,65109,83306,40785,37801,34012,39996,26846,44799,32258,18435	4.0569,3.62212,3.9047,3.53054,4.0847,3.48598,4.27468,3.35771,3.44647,3.54929,3.96187,3.22142,4.10016,5.11498,3.1088,4.75829,2.12374,2.89289,3.37738,3.9059,2.33322,5.09431,5.23259	3.7	Fail	Neural Network (Specific Model)	11	0.871	104314	245.8666	1787606	0.43	2121	None	metabat2_bins.455
MAG245	29.47	2.66	16	s20.ctg000030l,s2738.ctg003577l,s2957.ctg003824l,s3193.ctg004089l,s4138.ctg005156l,s4603.ctg005666l,s4794.ctg005871l,s5017.ctg006117l,s5044.ctg006149l,s5845.ctg007027l,s6190.ctg007401l,s7404.ctg008747l,s7434.ctg008783l,s7527.ctg008888l,s8733.ctg010247l,s9573.ctg011285l	15833,78265,84113,101783,64885,34079,41180,52771,43370,51386,38826,53767,16280,46219,38841,25334	4.09023,3.43509,3.34527,3.8504,4.46499,3.59949,3.73025,3.86553,2.63966,3.91541,2.96548,3.694,4.31116,3.18016,1.84195,5.48487	3.6	Fail	Neural Network (Specific Model)	11	0.827	52771	262.5259	786932	0.61	829	None	metabat2_bins.272_sub
MAG246	61.72	1.09	17	s288.ctg000468l,s378.ctg000602l,s925.ctg001396l,s1317.ctg001898l,s1684.ctg002345l,s2488.ctg003281l,s2590.ctg003406l,s2642.ctg003466l,s2884.ctg003743l,s3715.ctg004669l,s3914.ctg004899l,s4449.ctg005499l,s5188.ctg006311l,s5233.ctg006361l,s5670.ctg006838l,s6643.ctg007916l,s7892.ctg009310l	188204,235142,58127,71203,235441,93470,71318,76459,59845,163762,200859,60499,42020,108842,87634,105097,54885	3.17315,3.77708,4.03175,3.80484,3.93481,3.3105,2.88141,3.32806,3.99838,3.99356,4.00283,2.56203,3.93177,3.78977,3.53691,4.08257,3.99465	3.6	Fail	Gradient Boost (General Model)	11	0.822	163762	247.5500	1912807	0.62	2129	None	bin.127
MAG247	21.56	0.22	12	s319.ctg000509l,s728.ctg001113l,s1185.ctg001728l,s2869.ctg003727l,s4465.ctg005515l,s4584.ctg005646l,s5032.ctg006136l,s5556.ctg006710l,s5783.ctg006960l,s6877.ctg008169l,s6991.ctg008292l,s8749.ctg010267l	71158,60339,98712,65053,85174,53816,65119,35950,56818,74628,25240,27090	1.99437,3.42981,7.9848,2.64224,3.56719,5.75361,2.60769,2.00877,5.85666,2.79985,2.06544,2.41429	3.5	Fail	Neural Network (Specific Model)	11	0.842	65119	275.6068	719097	0.60	735	None	bin.525_sub
MAG248	79.67	2.97	35	s59.ctg000082l,s373.ctg000595l,s610.ctg000942l,s717.ctg001097l,s1164.ctg001697l,s1166.ctg001700l,s1389.ctg001984l,s1549.ctg002186l,s1685.ctg002346l,s2004.ctg002720l,s2075.ctg002808l,s64.ctg003033l,s2315.ctg003088l,s2525.ctg003326l,s2610.ctg003428l,s2667.ctg003494l,s2794.ctg003642l,s2837.ctg003693l,s3054.ctg003930l,s3126.ctg004015l,s3224.ctg004122l,s0.ctg004237l,s3419.ctg004342l,s3581.ctg004520l,s3727.ctg004683l,s4280.ctg005309l,s4333.ctg005366l,s4556.ctg005617l,s5395.ctg006533l,s5499.ctg006648l,s5519.ctg006670l,s7035.ctg008342l,s7090.ctg008405l,s8717.ctg010230l,s8786.ctg010310l	126591,361655,100641,196588,71237,76157,126339,241987,134259,52581,89935,130993,20736,52468,76246,36249,25933,138319,181600,87474,117393,144899,88384,99558,48297,104548,26440,40588,32317,143742,67923,50656,51752,31963,29964	3.31998,3.37571,3.92926,4.46983,3.28278,3.79907,3.27025,5.00553,3.10628,3.94515,3.31235,3.31907,2.65049,3.70156,4.62475,2.79941,2.40162,3.77858,4.04373,3.92821,3.88871,3.64772,3.43573,3.0721,4.11365,3.90224,2.73621,4.32771,2.39914,4.08301,4.46223,2.66133,4.65238,2.92415,2.17133	3.5	Fail	Neural Network (Specific Model)	11	0.870	126591	262.3970	3406412	0.48	3778	None	bin.59
MAG249	31.03	4.13	19	s1026.ctg001524l,s1037.ctg001537l,s1051.ctg001553l,s1305.ctg001882l,s1784.ctg002459l,s2056.ctg002784l,s2174.ctg002926l,s2771.ctg003615l,s3157.ctg004048l,s3443.ctg004368l,s4023.ctg005027l,s4901.ctg005984l,s5229.ctg006357l,s5458.ctg006601l,s5625.ctg006788l,s7442.ctg008791l,s8100.ctg009538l,s8392.ctg009860l,s9498.ctg011177l	68097,176324,172265,83842,34298,117944,77529,37629,120426,21318,46769,71641,106460,132027,32311,27850,34030,66975,22742	3.92556,3.34775,3.50568,3.76642,2.58572,4.33673,3.4269,4.09315,3.67789,4.62103,2.74984,3.42881,4.69907,3.56643,3.40677,3.62986,2.98326,2.77291,1.96831	3.4	Fail	Neural Network (Specific Model)	11	0.827	106460	244.8897	1450477	0.41	1641	None	metabat2_bins.368_sub
MAG250	61.02	19.99	45	s369.ctg000590l,s920.ctg001388l,s969.ctg001459l,s1455.ctg002064l,s1616.ctg002261l,s1899.ctg002596l,s2100.ctg002841l,s2272.ctg003038l,s2474.ctg003266l,s2616.ctg003434l,s3062.ctg003939l,s3283.ctg004187l,s3309.ctg004217l,s4025.ctg005029l,s4151.ctg005172l,s4292.ctg005322l,s4404.ctg005448l,s4630.ctg005695l,s4668.ctg005738l,s4711.ctg005784l,s4889.ctg005971l,s5004.ctg006099l,s5270.ctg006403l,s5410.ctg006549l,s5422.ctg006562l,s5564.ctg006719l,s5679.ctg006847l,s5914.ctg007096l,s5968.ctg007155l,s5984.ctg007171l,s6023.ctg007217l,s6085.ctg007283l,s6223.ctg007436l,s6346.ctg007574l,s6803.ctg008091l,s6980.ctg008281l,s7027.ctg008333l,s7133.ctg008452l,s7193.ctg008517l,s7947.ctg009371l,s8299.ctg009761l,s8460.ctg009936l,s8476.ctg009955l,s8700.ctg010211l,s9224.ctg010836l	172632,86171,24003,80397,43569,110183,99537,32745,54146,89178,29947,26354,96439,18365,36274,47754,40004,55270,59840,66528,36164,64490,32365,52995,73539,45635,35303,51610,21613,84376,46036,38192,82029,64938,48194,43309,36899,33789,34048,23824,65277,49040,29107,26825,36285	2.80596,4.16556,1.36784,2.22312,1.56821,4.57888,5.03452,4.06173,4.96057,4.63116,2.98664,2.4592,3.55807,1.84134,3.19117,1.60466,5.09093,2.64572,4.60157,4.29817,3.21206,4.00499,3.18814,2.45051,3.64014,3.23016,3.00048,3.39232,3.33555,3.11973,4.03511,5.49564,4.88825,2.28558,2.3727,3.27042,3.65961,2.04055,2.8102,5.05504,5.49569,3.02702,1.92454,3.74328,3.54941	3.4	Fail	Neural Network (Specific Model)	11	0.860	64490	260.9552	2425218	0.43	2679	None	bin.854
MAG251	55.15	5.56	21	s37.ctg000054l,s834.ctg001271l,s914.ctg001381l,s1371.ctg001965l,s1489.ctg002111l,s2158.ctg002909l,s2502.ctg003298l,s2689.ctg003523l,s3212.ctg004109l,s3251.ctg004152l,s3478.ctg004405l,s4016.ctg005019l,s4593.ctg005656l,s4597.ctg005660l,s4708.ctg005781l,s5254.ctg006384l,s6686.ctg007965l,s8424.ctg009896l,s9329.ctg010966l,s9471.ctg011137l,s9658.ctg011408l	78596,103406,70372,191867,52385,58658,114233,77656,124918,57666,64809,86286,62667,21794,41029,60797,95024,23173,23169,27219,17791	3.29094,2.88758,3.72607,4.87085,2.3315,7.69285,3.64554,2.51156,3.24491,3.43165,3.02309,3.10826,3.08332,1.65182,2.74221,3.31644,2.78741,1.66685,2.99327,3.17374,6.82121	3.4	Fail	Gradient Boost (General Model)	11	0.822	78596	247.0685	1453515	0.61	1620	None	bin.679
MAG252	45.66	5.66	29	s589.ctg000915l,s2182.ctg002934l,s2353.ctg003132l,s2565.ctg003373l,s2872.ctg003731l,s2944.ctg003808l,s3151.ctg004041l,s3400.ctg004321l,s3759.ctg004718c,s3780.ctg004746l,s3855.ctg004830l,s3863.ctg004838l,s4101.ctg005115l,s4374.ctg005412l,s4534.ctg005593l,s4576.ctg005638l,s5145.ctg006257l,s5587.ctg006745l,s6115.ctg007316l,s6336.ctg007562l,s6685.ctg007964l,s6873.ctg008165l,s7489.ctg008845l,s7944.ctg009367l,s8408.ctg009880l,s8747.ctg010265l,s8938.ctg010489l,s9558.ctg011268l,s9676.ctg011438l	40828,57348,55285,23729,148921,68452,24320,63437,93760,69223,37638,39789,49389,43231,41241,50255,32599,68462,37353,21999,59433,36096,25997,38973,20932,59676,32323,21504,20726	3.87241,3.71543,3.40969,2.76297,3.51865,4.11909,3.97753,3.29726,5.87069,2.97152,1.87249,2.7701,2.683,3.65437,3.26456,3.37006,3.08426,2.68439,3.48835,3.55751,2.67763,3.35097,2.26812,3.14571,1.67318,4.19538,3.30507,4.07984,3.46292	3.3	Fail	Neural Network (Specific Model)	11	0.829	55285	273.2801	1382919	0.59	1403	None	bin.114
MAG253	69.18	15.60	30	s23.ctg000033l,s144.ctg000222l,s252.ctg000403l,s331.ctg000526l,s0.ctg000759l,s581.ctg000900l,s788.ctg001200l,s1010.ctg001506l,s1248.ctg001808l,s0.ctg002010l,s1584.ctg002225l,s1793.ctg002470l,s2084.ctg002823l,s2677.ctg003508l,s2799.ctg003647l,s3016.ctg003888l,s3623.ctg004563l,s4088.ctg005099l,s4412.ctg005457l,s5189.ctg006313l,s6131.ctg007333l,s6337.ctg007564l,s6730.ctg008014l,s7053.ctg008362l,s7291.ctg008624l,s7555.ctg008922l,s7841.ctg009244l,s7981.ctg009408l,s8046.ctg009478l,s9417.ctg011074l	39992,35830,197837,120943,169888,129861,114016,181620,115172,119374,49221,31734,143062,50930,61779,198141,93483,67370,53254,94540,32423,64570,76772,75160,81048,54604,34130,31594,53794,29477	2.19113,3.76342,3.16151,3.83056,4.71267,4.17162,3.10658,3.75598,2.92857,3.73941,2.54258,2.88785,3.53284,3.0631,3.12921,3.83535,2.40307,3.3722,3.29243,2.67182,2.4061,3.65866,3.88361,3.16536,3.15272,5.54035,3.21686,2.65545,2.10296,3.41733	3.3	Fail	Neural Network (Specific Model)	11	0.806	115172	289.6945	2601619	0.37	2419	None	bin.139
MAG254	29.19	0.06	8	s375.ctg000597l,s2221.ctg002983l,s0.ctg004782l,s4347.ctg005381l,s4615.ctg005679l,s4805.ctg005882l,s5221.ctg006348l,s6797.ctg008085l	225076,147710,194073,34302,85393,40227,133716,26494	3.35754,2.67111,3.41757,2.51654,3.25166,4.85832,3.25033,3.22077	3.3	Fail	Neural Network (Specific Model)	11	0.844	147710	240.7109	886991	0.52	1041	None	metabat2_bins.546
MAG255	20.75	2.43	13	s1470.ctg002086l,s1540.ctg002170l,s2898.ctg003758l,s3068.ctg003946l,s3731.ctg004687l,s3736.ctg004693l,s5167.ctg006287l,s5700.ctg006870l,s6436.ctg007677l,s7066.ctg008376l,s7849.ctg009257l,s8332.ctg009797l,s9263.ctg010882l	87693,28458,278349,74197,43955,27108,48379,161706,35471,23295,27775,59374,31303	1.83794,2.02833,8.37382,3.39791,2.80984,2.85062,2.21406,4.66447,6.07287,1.70071,2.60043,2.50515,2.25705	3.3	Fail	Neural Network (Specific Model)	11	0.859	87693	294.3662	927063	0.56	904	None	bin.526_sub
MAG256	60.22	8.13	43	s131.ctg000197l,s295.ctg000478l,s383.ctg000610l,s672.ctg001037l,s996.ctg001492l,s1084.ctg001593l,s1213.ctg001762l,s1382.ctg001977l,s1411.ctg002012l,s1758.ctg002432l,s1846.ctg002531l,s1876.ctg002565l,s1920.ctg002620l,s2739.ctg003578l,s2770.ctg003614l,s2994.ctg003865l,s4033.ctg005038l,s4108.ctg005122l,s4145.ctg005166l,s4305.ctg005337l,s4396.ctg005439l,s4543.ctg005603l,s5309.ctg006442l,s5414.ctg006554l,s5710.ctg006880l,s6465.ctg007708l,s6573.ctg007836l,s6964.ctg008263l,s6990.ctg008291l,s7440.ctg008789l,s7531.ctg008893l,s7643.ctg009024l,s7646.ctg009028l,s7993.ctg009420l,s8064.ctg009496l,s8704.ctg010215l,s8756.ctg010275l,s8758.ctg010278l,s8802.ctg010330l,s9308.ctg010942l,s9523.ctg011218l,s9770.ctg011574l,s9792.ctg011610l	305347,49895,375642,55882,248835,31014,130392,247876,31828,187766,150748,34939,71432,24587,77533,55179,56712,41017,46593,88132,31457,171899,133728,57000,31386,27577,55069,21243,48560,35928,38750,19692,33537,15746,34231,25094,45233,29044,36043,29947,19522,41423,13879	4.96059,3.59264,5.89474,1.47621,4.20371,4.66514,5.50775,3.33778,1.54492,4.94714,4.20232,1.5473,4.44843,1.76994,5.20887,1.65233,4.1553,1.30408,2.04556,3.12351,2.63222,3.85701,4.79753,5.70568,1.8244,2.36887,3.53135,3.25165,5.94472,1.71946,2.05811,1.83722,2.90323,7.0125,1.34532,2.25329,1.62624,1.66727,1.63166,2.60842,2.4969,2.33128,7.19106	3.3	Fail	Neural Network (Specific Model)	11	0.871	150748	283.1068	3307337	0.46	3407	None	bin.107
MAG257	53.92	3.05	36	s596.ctg000924l,s613.ctg000946l,s1275.ctg001840l,s1437.ctg002043l,s2172.ctg002924l,s2185.ctg002937l,s2195.ctg002948l,s2265.ctg003030l,s2422.ctg003209l,s2823.ctg003675l,s2897.ctg003757l,s3195.ctg004091l,s3422.ctg004345l,s3600.ctg004539l,s3786.ctg004752l,s3978.ctg004972l,s4115.ctg005130l,s4542.ctg005602l,s4589.ctg005652l,s4636.ctg005704l,s4667.ctg005737l,s4770.ctg005847l,s4915.ctg005998l,s4957.ctg006046l,s5746.ctg006918l,s5761.ctg006935l,s5944.ctg007128l,s6134.ctg007336l,s6441.ctg007683l,s6725.ctg008009l,s7279.ctg008612l,s7585.ctg008952l,s8322.ctg009786l,s8389.ctg009857l,s8629.ctg010136l,s9662.ctg011413l	129967,68908,156311,52553,94398,40531,96899,154546,152245,128585,75845,57231,143903,259525,43188,78110,36201,96383,83254,9137,139669,34882,47777,36636,41011,56100,31513,94957,56362,47046,52473,23796,29274,36453,30950,46136	3.00096,4.4776,3.56779,3.0191,4.65858,3.37565,3.49427,3.1149,3.48155,3.48144,3.88525,2.90287,3.95278,5.12615,3.37925,3.42674,2.53291,3.3941,3.4286,1.35718,3.96346,2.10181,2.51798,1.88171,3.15403,5.5565,3.52843,2.80793,5.43594,3.88786,4.86121,2.12624,2.45766,1.6091,3.24432,2.82927	3.3	Fail	Neural Network (Specific Model)	11	0.869	96383	263.7078	2762755	0.50	3049	None	metabat2_bins.515
MAG258	89.06	0.19	41	s170.ctg000271l,s406.ctg000643l,s542.ctg000841l,s685.ctg001057l,s938.ctg001415l,s1136.ctg001663l,s1350.ctg001937l,s1531.ctg002158l,s1786.ctg002462l,s0.ctg002577l,s2212.ctg002970l,s2301.ctg003072l,s2307.ctg003079l,s2447.ctg003239l,s2467.ctg003259l,s0.ctg003441l,s2639.ctg003462l,s2729.ctg003566l,s2970.ctg003840l,s3256.ctg004157l,s3428.ctg004351l,s0.ctg004912l,s4113.ctg005127l,s4191.ctg005216l,s4440.ctg005488l,s4446.ctg005495l,s4555.ctg005615l,s4725.ctg005799l,s5113.ctg006224l,s5158.ctg006277l,s5175.ctg006297l,s5282.ctg006415l,s5402.ctg006541l,s5717.ctg006887l,s6737.ctg008021l,s6757.ctg008043l,s6938.ctg008234l,s6939.ctg008235l,s7104.ctg008421l,s7319.ctg008653l,s7402.ctg008745l	116738,89420,80535,42661,50259,64624,100033,50737,19250,114225,90516,21659,30581,83764,194023,122900,183169,27743,133893,116440,123318,105922,114919,116063,52894,45299,63907,50901,82961,52054,63908,58723,40958,51343,52540,34271,38283,120905,15803,62009,28888	3.86318,3.28845,3.36376,3.34991,4.43587,5.55398,3.21025,2.18105,2.87555,3.15046,3.54943,1.91283,2.57294,2.78606,4.01026,3.29174,3.25123,4.20531,3.75133,3.36338,2.91441,3.77284,4.80661,3.9067,3.79476,2.27826,2.35613,2.41579,2.5354,3.11255,3.44656,4.39194,4.32405,3.01578,2.52741,4.63835,3.66239,2.84064,3.95477,3.18107,2.64942	3.3	Fail	Gradient Boost (General Model)	11	0.874	105922	268.3262	3109039	0.47	3391	None	bin.61
MAG259	52.63	11.77	40	s117.ctg000176l,s178.ctg000286l,s207.ctg000326l,s453.ctg000708l,s497.ctg000774l,s1890.ctg002584l,s0.ctg002686l,s1991.ctg002704l,s2049.ctg002777l,s2181.ctg002933l,s2343.ctg003121l,s2567.ctg003377l,s2621.ctg003439l,s2793.ctg003641l,s3136.ctg004026l,s3299.ctg004203l,s3583.ctg004522l,s4663.ctg005732l,s4730.ctg005804l,s5226.ctg006353l,s5250.ctg006380l,s5327.ctg006462l,s5350.ctg006485l,s5832.ctg007013l,s5924.ctg007107l,s6489.ctg007734l,s6534.ctg007790l,s6581.ctg007845l,s6601.ctg007867l,s6844.ctg008135l,s7020.ctg008326l,s7180.ctg008503l,s7916.ctg009336l,s7949.ctg009373l,s7971.ctg009397l,s8031.ctg009461l,s8469.ctg009947l,s8620.ctg010126l,s8697.ctg010207l,s9296.ctg010922l	36007,59547,59998,46164,9157,17090,108144,19227,31149,23345,100062,60850,16442,29286,30958,54001,40103,31265,29061,37518,17273,14734,44549,25273,31279,32229,44919,25095,14222,58411,41459,34826,19081,30184,44322,30593,24716,76770,40392,44879	6.07259,7.66421,2.83249,4.10573,1.5589,3.40638,8.77869,5.2708,4.13546,3.34309,3.47083,4.69282,3.00037,2.6574,2.70858,5.14018,4.1266,2.44011,3.73059,2.46034,1.5464,3.76241,2.47039,2.41607,1.33281,2.44344,1.51609,1.65027,1.58869,2.17813,3.46554,7.52272,1.96566,1.79949,1.9279,2.09759,2.9632,3.23284,3.84732,1.88866	3.3	Fail	Gradient Boost (General Model)	11	0.844	44322	246.5949	1534580	0.56	1760	None	bin.943
MAG260	47.52	5.89	28	s309.ctg000498l,s320.ctg000511l,s682.ctg001054l,s805.ctg001229l,s1303.ctg001879l,s2367.ctg003152l,s2701.ctg003537l,s3115.ctg004001l,s3357.ctg004272l,s3377.ctg004293l,s3883.ctg004861l,s4420.ctg005466l,s4467.ctg005517l,s4979.ctg006069l,s5043.ctg006148l,s5390.ctg006527l,s5480.ctg006629l,s6152.ctg007356l,s7178.ctg008501l,s7759.ctg009155l,s7876.ctg009288l,s7879.ctg009293l,s7898.ctg009316l,s8334.ctg009799l,s8390.ctg009858l,s8643.ctg010151l,s8894.ctg010440l,s9791.ctg011608l	137362,31058,174078,60754,127367,102065,98803,24699,141631,24403,22840,26612,48594,19904,30859,31893,17605,18890,41761,28070,37510,26197,33452,35683,23473,34793,21772,14610	3.89253,1.96833,7.20533,5.09013,3.29702,5.0294,4.25841,1.8859,5.02894,1.20641,3.16545,8.82511,1.91592,6.05548,2.15149,3.83981,3.10753,4.1198,1.89101,1.6086,1.44291,1.57385,2.00375,2.56486,1.88745,1.45827,1.91476,3.76093	3.2	Fail	Neural Network (Specific Model)	11	0.849	98803	263.1315	1436738	0.36	1551	None	bin.144
MAG261	53.12	4.73	24	s853.ctg001297l,s993.ctg001487l,s1124.ctg001646l,s1390.ctg001985l,s1681.ctg002342l,s1955.ctg002663l,s2310.ctg003082l,s2377.ctg003162l,s2697.ctg003533l,s3176.ctg004071l,s3858.ctg004833l,s3871.ctg004849l,s4424.ctg005470l,s4516.ctg005574l,s4760.ctg005837l,s5415.ctg006555l,s5741.ctg006913l,s6162.ctg007369l,s6283.ctg007504l,s8034.ctg009465l,s8456.ctg009932l,s8660.ctg010169l,s8881.ctg010425l,s9262.ctg010881l	309707,86984,27728,291262,68022,144275,149614,195426,111471,22111,25654,37400,32273,66756,26834,129963,123878,21476,43651,22698,62297,14454,19206,16791	4.21208,4.51027,3.5376,3.5678,2.7373,4.6042,4.4879,3.5428,2.73419,3.34725,1.83708,4.36795,2.01955,3.5553,5.75116,2.5597,3.86114,2.49798,2.50452,1.48417,3.0871,2.70694,2.68063,2.35989	3.2	Fail	Neural Network (Specific Model)	11	0.828	144275	263.7517	2049931	0.67	2155	None	bin.116
MAG262	73.24	3.75	29	s649.ctg001003l,s1035.ctg001534l,s1108.ctg001630l,s1896.ctg002592l,s1984.ctg002697l,s2131.ctg002880l,s2716.ctg003552l,s2925.ctg003788l,s3373.ctg004288l,s3719.ctg004673l,s3964.ctg004956l,s4287.ctg005316l,s4494.ctg005551l,s4551.ctg005611l,s4841.ctg005919l,s5387.ctg006524l,s6258.ctg007477l,s6500.ctg007746l,s6823.ctg008113l,s6831.ctg008122l,s7624.ctg009000l,s7822.ctg009223l,s7953.ctg009377l,s7966.ctg009392l,s8248.ctg009702l,s8653.ctg010161l,s8868.ctg010411l,s9387.ctg011036l,s9462.ctg011127l	389036,43314,38912,63972,71446,58879,180994,49962,57959,40217,30795,110760,48587,21393,65260,17134,45517,49527,37904,22043,56106,25292,25357,32104,35376,16958,60531,32364,16359	3.99602,3.41069,3.12102,2.48004,2.98624,1.91389,4.03119,3.5317,2.70442,2.98121,4.61602,2.85631,4.40597,2.52803,3.66131,2.16592,2.61739,3.89368,4.37093,2.5092,3.42376,3.10604,4.81319,1.91309,2.89863,3.14303,3.06767,4.41594,3.58313	3.2	Fail	Gradient Boost (General Model)	11	0.841	63972	267.1876	1744058	0.59	1839	None	bin.102
MAG263	75.89	1.65	27	s237.ctg000376l,s642.ctg000989l,s779.ctg001186l,s860.ctg001306l,s946.ctg001425l,s2228.ctg002990l,s2234.ctg002996l,s2606.ctg003424l,s2684.ctg003516l,s3077.ctg003958l,s3374.ctg004289l,s3843.ctg004816l,s3853.ctg004828l,s4250.ctg005279l,s4291.ctg005321l,s4328.ctg005361l,s4563.ctg005624l,s5709.ctg006879l,s5858.ctg007040l,s6208.ctg007421l,s6701.ctg007981l,s7192.ctg008516l,s7484.ctg008839l,s7512.ctg008871l,s7773.ctg009170l,s9287.ctg010911l,s9484.ctg011158l	86602,285752,267705,168856,115978,109515,75566,66071,67026,95815,79532,70652,60220,63854,101027,32981,111874,49694,81462,34069,17332,17446,34046,35769,24794,13512,40306	4.08021,4.00751,4.35311,3.83357,3.29186,4.68259,3.69036,3.47707,3.82928,3.71504,3.43915,3.53523,2.39471,3.9659,3.93754,2.421,3.16456,2.31798,4.53367,3.68077,1.9553,2.6254,1.71988,3.04767,2.07125,0.853989,2.42024	3.2	Fail	Neural Network (Specific Model)	11	0.882	101027	275.0866	2207456	0.41	2368	None	bin.87
MAG264	63.30	7.60	21	s215.ctg000336l,s807.ctg001233l,s957.ctg001444l,s1354.ctg001942l,s1606.ctg002251l,s2387.ctg003172l,s2534.ctg003339l,s3650.ctg004597l,s4002.ctg005001l,s4341.ctg005375l,s4343.ctg005377l,s4466.ctg005516l,s5154.ctg006269l,s6712.ctg007993l,s7207.ctg008533l,s7400.ctg008743l,s7628.ctg009005l,s7752.ctg009147l,s8132.ctg009570l,s9153.ctg010754l,s9182.ctg010786l	57854,39417,102006,97405,98027,214536,171023,49293,53859,45264,96297,95078,38334,52051,35580,29967,40076,23282,57774,32630,27616	2.42968,3.40887,3.39471,3.44462,4.52867,3.69264,3.13697,3.15813,3.50634,2.61302,2.62462,3.7675,2.52134,1.70089,2.20765,2.01824,3.26657,1.85851,3.74738,3.89621,4.75024	3.1	Fail	Gradient Boost (General Model)	11	0.845	96297	251.1443	1457369	0.34	1642	None	bin.137
MAG265	67.54	0.16	36	s127.ctg000190l,s527.ctg000819l,s1007.ctg001503l,s1029.ctg001527l,s1049.ctg001551l,s1592.ctg002234l,s1611.ctg002256l,s1652.ctg002305l,s2047.ctg002775l,s2141.ctg002890l,s2423.ctg003210l,s2460.ctg003252l,s2463.ctg003255l,s2522.ctg003323l,s2615.ctg003433l,s2691.ctg003526l,s3160.ctg004052l,s3498.ctg004427l,s3640.ctg004585l,s4044.ctg005050l,s4257.ctg005286l,s4621.ctg005686l,s4846.ctg005924l,s5302.ctg006435l,s5324.ctg006459l,s5588.ctg006746l,s6121.ctg007323l,s6495.ctg007741l,s6647.ctg007920l,s6746.ctg008031l,s6965.ctg008264l,s7014.ctg008320l,s7503.ctg008861l,s7613.ctg008988l,s8038.ctg009469l,s9202.ctg010810l	58027,21711,211117,22109,37134,119250,56101,46747,53898,59794,31978,44426,81187,21099,196743,45792,138315,29301,129404,41444,46402,44185,44400,43324,33205,109690,64552,25793,66575,99264,28764,25166,34673,34869,20110,18154	3.0152,4.7752,3.05609,4.28134,3.24646,3.6442,3.89423,3.16542,3.09422,3.50964,3.21528,2.43884,2.93704,2.02005,3.39072,2.61702,4.01597,3.06772,3.61366,3.03877,3.29357,1.92824,3.29473,3.74765,3.2786,3.01858,3.8839,2.7209,3.16191,2.72503,2.59104,2.99816,3.2231,2.44961,2.39664,2.6553	3.1	Fail	Neural Network (Specific Model)	11	0.835	66575	259.7383	2184703	0.67	2354	None	bin.122
MAG266	48.88	7.00	31	s328.ctg000523l,s1651.ctg002304l,s1885.ctg002578l,s2116.ctg002862l,s2466.ctg003258l,s2995.ctg003866l,s3409.ctg004331l,s3806.ctg004775l,s3957.ctg004949l,s4005.ctg005004l,s4460.ctg005510l,s5027.ctg006129l,s5340.ctg006475l,s5487.ctg006636l,s5655.ctg006820l,s5910.ctg007092l,s6038.ctg007234l,s6092.ctg007291l,s6130.ctg007332l,s6453.ctg007695l,s6494.ctg007740l,s6507.ctg007753l,s6555.ctg007815l,s6971.ctg008271l,s7089.ctg008404l,s7761.ctg009157l,s8239.ctg009692l,s8368.ctg009834l,s8916.ctg010465l,s9489.ctg011165l,s9737.ctg011524l	49498,55127,72135,40167,24893,34215,25539,43958,63924,36835,34951,27994,62486,34308,42732,19849,19518,18761,72940,34749,42247,22241,35706,27712,17978,18803,11577,41213,37436,42446,35911	3.58274,3.1001,2.22796,2.94677,4.73188,1.7796,5.18776,3.66002,4.20899,2.94611,3.82196,4.02212,2.83156,4.05545,3.69442,2.2162,3.04115,2.67353,2.54714,2.87121,1.95971,2.83889,2.51012,2.08363,2.44778,2.78293,4.66474,1.80642,3.37065,2.84457,5.69293	3.1	Fail	Gradient Boost (General Model)	11	0.854	41213	241.0946	1147849	0.48	1364	None	bin.255
MAG267	68.32	0.69	26	s31.ctg000044l,s234.ctg000371l,s278.ctg000451l,s626.ctg000961l,s1102.ctg001622l,s0.ctg001781l,s1394.ctg001989l,s1590.ctg002232l,s1940.ctg002642l,s2046.ctg002774l,s2577.ctg003389l,s2894.ctg003754l,s2902.ctg003762l,s3305.ctg004211l,s3323.ctg004232l,s3417.ctg004340l,s3547.ctg004477l,s4186.ctg005210l,s4721.ctg005795l,s4909.ctg005992l,s5130.ctg006241l,s5523.ctg006675l,s8139.ctg009578l,s8251.ctg009706l,s8957.ctg010509l,s9362.ctg011005l	68935,54597,75602,21504,126847,122184,71389,115051,100317,27065,171241,191750,55642,74803,110056,170913,106272,44951,112563,37120,37406,56031,37460,21747,31981,11509	1.93829,2.6782,4.10327,2.68015,4.46052,3.39019,3.71423,3.30119,2.77402,2.81055,4.22508,3.3793,2.54975,2.98097,3.45779,3.60161,3.11715,3.44843,3.20514,3.16032,3.9311,2.50581,2.96971,3.88086,2.22085,0.504886	3.1	Fail	Gradient Boost (General Model)	11	0.831	110056	262.6607	2054936	0.59	2175	None	bin.111
MAG268	62.25	19.16	35	s26.ctg000037l,s513.ctg000797c,s635.ctg000976l,s726.ctg001109c,s1969.ctg002678l,s2015.ctg002734l,s2036.ctg002763l,s2040.ctg002767l,s2631.ctg003452l,s2761.ctg003604l,s3388.ctg004307l,s3664.ctg004613l,s3757.ctg004716l,s4319.ctg005351l,s4439.ctg005487l,s4816.ctg005893l,s5088.ctg006197l,s5294.ctg006427l,s5738.ctg006910l,s5900.ctg007082l,s6051.ctg007248l,s6141.ctg007344l,s7039.ctg008346l,s7058.ctg008367l,s7132.ctg008451l,s7188.ctg008512l,s7374.ctg008714l,s7589.ctg008957l,s8105.ctg009543l,s8153.ctg009593l,s8279.ctg009738l,s9024.ctg010595l,s9035.ctg010608l,s9067.ctg010646l,s9753.ctg011550l	28010,330013,66561,405344,25412,86635,28936,102692,117198,109871,159516,21064,14797,29942,77659,39058,46340,37286,43540,73066,71089,26447,19641,31452,25146,43273,39028,30807,61031,77682,34485,43281,13261,19220,27317	2.41482,8.46124,3.24067,8.12211,1.68799,8.23003,2.72028,4.27645,5.74072,2.31959,5.95632,2.61217,1.408,2.93193,2.48961,2.22692,2.92414,1.81735,2.82249,3.07027,3.32545,1.79287,2.43825,1.66306,2.43019,2.84952,2.06595,1.9269,3.39622,2.97856,1.65895,3.75839,0.990237,3.09649,1.27497	3.1	Fail	Gradient Boost (General Model)	11	0.835	102692	259.1900	2406100	0.57	2595	None	bin.890
MAG269	82.72	0.01	24	s101.ctg000152l,s557.ctg000865l,s841.ctg001281l,s2244.ctg003006l,s2723.ctg003560l,s2806.ctg003656l,s2865.ctg003723l,s3529.ctg004459l,s3947.ctg004937l,s4058.ctg005066l,s4163.ctg005185l,s4224.ctg005252l,s4546.ctg005606l,s5236.ctg006364l,s5430.ctg006571l,s5536.ctg006689l,s5773.ctg006949l,s6052.ctg007249l,s7414.ctg008759l,s7793.ctg009193l,s8213.ctg009661l,s8635.ctg010142l,s9421.ctg011078l,s9686.ctg011449l	78338,268447,108081,25493,122994,58042,78809,53292,81342,31347,35262,148826,37287,76135,33619,28073,51959,30743,76526,69999,35192,21443,19134,20057	3.25253,4.39166,3.6811,2.78061,3.87706,4.24534,3.85998,3.82551,3.67987,2.11184,2.84492,4.02074,3.06885,2.90922,2.73441,3.3414,3.09475,3.15641,3.83344,2.39124,3.06572,1.74564,1.77639,2.57231	3.1	Fail	Gradient Boost (General Model)	11	0.871	78809	280.0623	1590440	0.60	1654	None	bin.69
MAG270	70.58	0.04	24	s924.ctg001393l,s933.ctg001405l,s1306.ctg001884l,s1689.ctg002350l,s2017.ctg002736l,s2254.ctg003016l,s2564.ctg003372l,s2644.ctg003470l,s2678.ctg003510l,s3404.ctg004326l,s3526.ctg004456l,s4314.ctg005346l,s4707.ctg005780l,s4814.ctg005891l,s5038.ctg006143l,s5508.ctg006658l,s5895.ctg007077l,s6934.ctg008230l,s7023.ctg008329l,s7398.ctg008740l,s7592.ctg008960l,s7672.ctg009056l,s9229.ctg010841l,s9563.ctg011274l	306103,153194,42677,103524,84577,140952,127723,79176,28954,127492,41381,28562,72286,42468,54792,30282,29033,25707,41985,75335,39264,31932,32871,29932	3.89574,3.3027,2.03941,3.45138,2.87209,2.84634,3.81381,3.0639,2.09228,2.47098,2.67939,2.93457,3.05096,2.76773,2.88811,3.32228,3.70173,2.8098,2.88646,3.5072,2.71898,2.93027,3.38798,3.86948	3.0	Fail	Gradient Boost (General Model)	11	0.839	103524	251.4679	1770202	0.53	1979	None	bin.80
MAG271	79.96	1.18	14	s381.ctg000607l,s447.ctg000701l,s1663.ctg002318l,s2157.ctg002908l,s3567.ctg004502l,s4904.ctg005987l,s5005.ctg006100l,s5955.ctg007142l,s6101.ctg007301l,s7096.ctg008412l,s8142.ctg009581l,s9003.ctg010565l,s9007.ctg010570l,s9061.ctg010639l	145640,86560,89322,156901,105707,28681,63672,41255,69219,116386,50008,34884,62972,26432	3.07233,2.54089,3.46537,3.06381,4.31065,1.97182,3.04507,1.76738,3.34166,3.08023,4.17255,2.11821,4.07128,2.66441	3.0	Fail	Gradient Boost (General Model)	11	0.868	89322	226.7169	1077639	0.25	1381	None	metabat2_bins.321
MAG272	72.17	0.85	34	s217.ctg000341l,s652.ctg001007l,s782.ctg001192l,s863.ctg001310l,s880.ctg001335l,s1436.ctg002042l,s1670.ctg002326l,s1705.ctg002368l,s1770.ctg002444l,s1823.ctg002507l,s1832.ctg002517l,s1983.ctg002695l,s2117.ctg002863l,s2179.ctg002931l,s2283.ctg003050l,s2526.ctg003327l,s3817.ctg004789l,s4041.ctg005046l,s4082.ctg005091l,s4147.ctg005168l,s4635.ctg005702l,s4758.ctg005835l,s5053.ctg006160l,s5329.ctg006464l,s5919.ctg007102l,s6007.ctg007199l,s6022.ctg007216l,s6691.ctg007970l,s6758.ctg008044l,s7074.ctg008388l,s7695.ctg009085l,s7826.ctg009227l,s9050.ctg010628l,s9100.ctg010687l	79465,85762,122732,110052,182383,27833,29068,99987,184969,72650,69073,333036,23463,110251,102565,30483,45839,82068,132220,25638,16821,48848,19568,65432,40587,51086,26532,55320,27334,85430,76662,26949,26557,23160	2.66184,2.53685,2.94344,2.99222,3.05218,3.87733,2.20807,3.14779,4.73381,2.78772,2.74561,4.12341,2.58602,3.69309,3.52687,3.39211,4.27177,3.84177,2.46674,3.5636,2.75556,3.42934,2.15403,3.71098,1.98929,2.92304,1.95311,3.01314,3.29782,3.13354,2.92418,2.27714,3.42333,1.91243	3.0	Fail	Neural Network (Specific Model)	11	0.878	102565	303.2916	2539823	0.48	2459	None	bin.93
MAG273	74.27	0.66	29	s145.ctg000224l,s174.ctg000280l,s266.ctg000434l,s516.ctg000802l,s1683.ctg002344l,s1731.ctg002400l,s2751.ctg003593l,s2853.ctg003710l,s3053.ctg003929l,s3172.ctg004067l,s3347.ctg004260l,s3590.ctg004529l,s4237.ctg005266l,s4955.ctg006044l,s5732.ctg006903l,s5776.ctg006953l,s6006.ctg007197l,s6110.ctg007310l,s6205.ctg007417l,s6276.ctg007497l,s6456.ctg007699l,s6804.ctg008092l,s7237.ctg008567l,s7348.ctg008686l,s7850.ctg009258l,s8669.ctg010178l,s8839.ctg010378l,s8907.ctg010455l,s9076.ctg010656l	30528,58560,99908,153356,25773,75653,151144,144823,103896,63933,70940,110929,48160,27196,23387,82069,33384,63094,26323,142140,70313,56514,50392,52174,32661,26224,32151,31963,25437	2.92867,4.2376,4.17848,3.56137,2.64145,4.09076,3.81142,3.60409,2.85481,4.01685,3.5022,3.27298,2.08209,1.84109,1.98576,2.83819,3.06656,3.08757,2.15638,3.56772,2.76197,2.81508,1.9869,4.14782,2.48337,2.05047,1.66104,2.55062,1.67881	2.9	Fail	Gradient Boost (General Model)	11	0.839	82069	256.6719	1913025	0.32	2094	None	bin.89
MAG274	44.98	4.27	28	s177.ctg000285l,s894.ctg001355l,s990.ctg001484l,s1301.ctg001876l,s1330.ctg001913l,s1564.ctg002202l,s1577.ctg002218l,s2448.ctg003240l,s2654.ctg003480l,s2916.ctg003778l,s3007.ctg003878l,s3047.ctg003923l,s3372.ctg004287l,s4078.ctg005087l,s4970.ctg006059l,s5177.ctg006299l,s5980.ctg007167l,s6047.ctg007244l,s7060.ctg008369l,s7582.ctg008949l,s8076.ctg009512l,s8204.ctg009650l,s8252.ctg009707l,s8421.ctg009893l,s8692.ctg010201l,s8788.ctg010312l,s9431.ctg011091l,s9525.ctg011220l	121263,33803,41649,169666,164943,77414,56572,23743,88096,108817,26005,24321,48475,108209,32310,38005,42855,22460,108538,35524,34261,33232,18996,26748,38873,24639,22092,17957	3.799,3.46917,2.32473,3.3672,3.5497,3.2464,3.65471,4.28907,3.70631,3.52108,4.1549,2.14753,2.80472,3.99198,2.23924,3.26541,2.97705,1.94796,2.83039,2.7631,2.72097,2.6048,3.03407,2.82897,1.52049,3.0744,1.58773,1.9708	2.9	Fail	Gradient Boost (General Model)	11	0.838	88096	271.6180	1589466	0.60	1644	None	bin.179
MAG275	55.02	1.38	21	s313.ctg000502l,s857.ctg001302l,s1641.ctg002292l,s1821.ctg002504l,s3111.ctg003996l,s3164.ctg004058l,s3394.ctg004314l,s3956.ctg004948l,s4456.ctg005506l,s5050.ctg006157l,s5392.ctg006529l,s5675.ctg006843l,s5730.ctg006901l,s5950.ctg007135l,s6070.ctg007267l,s6660.ctg007933l,s7661.ctg009045l,s7783.ctg009181l,s8543.ctg010033l,s8593.ctg010093l,s8860.ctg010402l	147502,37666,49670,173074,64550,38511,57638,91034,36524,45508,28311,129987,24858,54703,120085,20442,46620,30950,36621,60879,58151	2.76334,1.98331,2.01601,4.00343,3.23325,4.19489,4.04239,3.46485,3.91772,1.49888,3.11012,3.12039,2.11551,2.26803,3.11159,2.93771,2.97202,4.35935,2.75915,1.60388,3.51828	2.9	Fail	Gradient Boost (General Model)	11	0.816	64550	219.1059	1353284	0.38	1690	None	bin.132
MAG276	66.60	1.83	26	s479.ctg000750l,s756.ctg001156l,s1098.ctg001617l,s1500.ctg002124l,s1536.ctg002166l,s1614.ctg002259l,s1825.ctg002509l,s1892.ctg002586l,s2099.ctg002840l,s3420.ctg004343l,s3844.ctg004817l,s4150.ctg005171l,s4218.ctg005244l,s4312.ctg005344l,s4360.ctg005395l,s4695.ctg005766l,s4746.ctg005823l,s4759.ctg005836l,s4777.ctg005854l,s5098.ctg006209l,s5873.ctg007055l,s6783.ctg008070l,s6908.ctg008204l,s7061.ctg008371l,s7659.ctg009043l,s8358.ctg009824l	88985,62987,41502,246176,74752,215025,109496,51783,56267,195862,25317,33089,32926,48230,91512,193537,51256,55917,35096,124039,70653,17286,29535,68310,37406,38470	3.41099,3.70116,1.68667,3.49815,3.5032,3.19583,3.51156,3.13716,2.64836,3.40007,2.54699,3.11345,2.09977,2.44201,3.10771,3.07782,3.79308,2.41223,2.06782,3.1555,4.29936,2.24376,1.61848,3.27217,3.49444,3.25172	2.9	Fail	Neural Network (Specific Model)	11	0.882	109496	266.5062	2095414	0.47	2321	None	bin.68
MAG277	76.42	2.54	31	s816.ctg001242l,s958.ctg001445l,s1207.ctg001756l,s1217.ctg001767l,s1267.ctg001831l,s1329.ctg001912l,s1480.ctg002099l,s1585.ctg002227l,s1915.ctg002613l,s2219.ctg002981l,s2348.ctg003127l,s2742.ctg003582l,s3146.ctg004036l,s3163.ctg004057l,s3673.ctg004622l,s4481.ctg005534l,s4686.ctg005757l,s4712.ctg005785l,s4785.ctg005862l,s6098.ctg007298l,s6403.ctg007640l,s6650.ctg007923l,s6687.ctg007966l,s7010.ctg008315l,s7209.ctg008535l,s7813.ctg009213l,s8097.ctg009535l,s8230.ctg009682l,s8328.ctg009793l,s8683.ctg010192l,s8710.ctg010221l	139925,77493,83005,155824,95433,230345,79666,310439,137475,10034,50007,23739,58760,46006,47244,18940,130845,44002,20020,29995,49565,101701,58477,19875,105088,31006,34250,37790,21934,31118,51758	3.23534,3.37331,3.03773,3.49905,3.54077,3.23218,3.45943,2.97738,3.84435,1.9222,1.87011,2.06372,2.01114,3.76125,3.48004,1.69894,3.27552,1.94589,2.7309,1.96378,3.05247,3.3996,4.30723,2.63965,3.14108,2.27389,3.79431,3.62917,2.20253,1.3741,3.67536	2.9	Fail	Gradient Boost (General Model)	11	0.840	105088	250.2025	2331759	0.58	2622	None	bin.78
MAG278	22.22	0.37	12	s634.ctg000975l,s1884.ctg002576l,s3066.ctg003943l,s3646.ctg004593l,s3939.ctg004928l,s4168.ctg005191l,s5936.ctg007120l,s6958.ctg008255l,s7259.ctg008592l,s8382.ctg009848l,s8508.ctg009989l,s9221.ctg010832l	115094,41244,109241,37297,46054,57059,53416,34108,27036,38267,40175,31658	3.77392,2.71001,2.31161,2.61852,2.4475,5.71755,2.51299,1.79769,2.16462,2.07823,2.003,5.76596	2.9	Fail	Neural Network (Specific Model)	11	0.849	53416	251.1499	630649	0.34	714	None	bin.185
MAG279	78.66	6.23	31	s179.ctg000287l,s356.ctg000568l,s566.ctg000878l,s658.ctg001019l,s813.ctg001239l,s1250.ctg001810l,s1281.ctg001848l,s1630.ctg002278l,s1745.ctg002417l,s1782.ctg002457l,s1811.ctg002491l,s1921.ctg002621l,s2971.ctg003841l,s3143.ctg004033l,s3469.ctg004396l,s3512.ctg004441l,s3864.ctg004840l,s3996.ctg004994l,s4840.ctg005918l,s4943.ctg006031l,s4960.ctg006049l,s5295.ctg006428l,s5366.ctg006501l,s5440.ctg006582l,s5692.ctg006862l,s5918.ctg007101l,s6103.ctg007303l,s6247.ctg007463l,s6677.ctg007955l,s7686.ctg009075l,s7863.ctg009273l	187720,77667,284783,71616,14567,114722,99637,46937,49110,27392,79911,188633,128925,62456,56186,183598,35876,32762,36019,56598,35183,72743,80220,86449,65149,20417,30380,28059,35545,42709,25326	3.33332,4.10402,3.88858,3.16475,1.62107,4.13452,4.59094,2.82316,3.78192,3.54449,3.58542,2.94414,2.9172,2.22049,2.81185,3.19692,2.18628,2.09742,2.3762,2.93428,1.43419,3.37334,2.47404,3.82784,2.87501,1.8243,2.46189,1.31158,1.55864,1.8796,2.55064	2.8	Fail	Neural Network (Specific Model)	11	0.869	99637	242.3237	2357295	0.44	2833	None	bin.104
MAG280	69.91	7.50	30	s405.ctg000641l,s428.ctg000674l,s1919.ctg002618l,s1941.ctg002643l,s1956.ctg002664l,s2020.ctg002740l,s2140.ctg002889l,s2257.ctg003019l,s2298.ctg003068l,s2345.ctg003123l,s2535.ctg003340l,s2655.ctg003481l,s0.ctg004164l,s4007.ctg005007l,s4118.ctg005133l,s4322.ctg005354l,s4509.ctg005567l,s4753.ctg005830l,s4930.ctg006017l,s5129.ctg006240l,s5868.ctg007050l,s5912.ctg007094l,s6049.ctg007246l,s6072.ctg007269l,s7160.ctg008482l,s7318.ctg008652l,s7403.ctg008746l,s8306.ctg009769l,s8875.ctg010418l,s9635.ctg011372l	169173,103433,55752,50320,107795,202542,42071,25917,147074,42675,94948,31750,164503,67181,82060,179550,51901,56966,22127,21265,52002,22695,73670,21832,58324,86041,81467,48798,35020,23756	4.10192,2.71383,1.52727,2.96602,3.48708,3.68369,2.14933,2.14542,3.40355,1.97089,3.71957,2.95794,3.02093,1.97285,2.68767,3.21532,1.72963,3.03573,2.62279,2.94937,3.86539,2.88383,3.11621,3.35546,3.34644,2.80134,2.75335,2.20075,2.20588,1.48767	2.8	Fail	Gradient Boost (General Model)	11	0.810	94948	203.2377	2222608	0.46	2978	None	bin.98
MAG281	74.59	0.14	48	s355.ctg000566l,s900.ctg001362l,s916.ctg001384l,s1137.ctg001664l,s1286.ctg001855l,s1628.ctg002275l,s1801.ctg002480l,s2225.ctg002987l,s2243.ctg003005l,s2292.ctg003061l,s2482.ctg003274l,s2605.ctg003423l,s2766.ctg003610l,s3055.ctg003931l,s3217.ctg004115l,s3234.ctg004132l,s3733.ctg004689l,s3885.ctg004863l,s4124.ctg005140l,s4289.ctg005318l,s4295.ctg005326l,s4426.ctg005472l,s4588.ctg005651l,s4606.ctg005670l,s4880.ctg005962l,s5079.ctg006188l,s5127.ctg006238l,s5554.ctg006707l,s5775.ctg006952l,s5836.ctg007017l,s6151.ctg007354l,s6187.ctg007398l,s6541.ctg007798l,s6562.ctg007823l,s6622.ctg007890l,s6931.ctg008227l,s7097.ctg008413l,s7112.ctg008429l,s7208.ctg008534l,s7282.ctg008615l,s7412.ctg008757l,s7546.ctg008912l,s7854.ctg009262l,s8021.ctg009451l,s8082.ctg009519l,s8566.ctg010060l,s8845.ctg010385l,s9513.ctg011204l	65203,168813,25139,68858,35508,43872,20939,53359,76895,37472,71332,45441,61764,21009,55576,195322,100064,57721,59451,54243,21652,95991,38531,75587,74929,28051,31735,27685,36334,31549,34708,26718,110501,47406,70897,30220,58639,58932,19449,132844,60225,39954,31306,26985,39850,40809,40243,26903	2.5898,3.52591,3.01569,3.93801,2.50453,1.95881,3.06455,2.14424,2.80614,2.10093,3.04365,2.33015,3.18056,1.6532,2.20741,3.27186,3.1485,3.56198,2.67699,3.74736,1.87662,3.52596,2.74154,2.38848,2.6094,2.11207,2.66547,2.8272,2.88127,2.2088,2.16931,2.32317,3.46196,3.57952,3.41728,2.6566,2.78654,2.8516,2.97627,2.47646,2.35849,2.11283,2.02622,1.8414,2.65131,3.38127,2.45497,1.95615	2.7	Fail	Gradient Boost (General Model)	11	0.849	61764	296.0238	2676614	0.43	2568	None	bin.90
MAG282	58.65	1.20	54	s283.ctg000463l,s286.ctg000466l,s336.ctg000534l,s614.ctg000947l,s680.ctg001051l,s804.ctg001228l,s887.ctg001342l,s1154.ctg001685l,s1309.ctg001889l,s1318.ctg001899l,s1399.ctg001995l,s1800.ctg002479l,s2194.ctg002947l,s2347.ctg003126l,s2464.ctg003256l,s2658.ctg003484l,s2755.ctg003597l,s3296.ctg004200l,s3322.ctg004231l,s3700.ctg004653l,s3940.ctg004929l,s4182.ctg005206l,s4213.ctg005239l,s4256.ctg005285l,s4377.ctg005416l,s4577.ctg005639l,s4775.ctg005852l,s5148.ctg006260l,s5183.ctg006306l,s5230.ctg006358l,s5268.ctg006400l,s5359.ctg006494l,s5633.ctg006796l,s5707.ctg006877l,s5974.ctg007161l,s6010.ctg007202l,s6125.ctg007327l,s6320.ctg007545l,s6380.ctg007615l,s6760.ctg008046l,s6942.ctg008238l,s7126.ctg008445l,s7149.ctg008470l,s7231.ctg008561l,s7453.ctg008804l,s7479.ctg008832l,s7494.ctg008850l,s7608.ctg008981l,s7679.ctg009066l,s7977.ctg009403l,s8414.ctg009886l,s8646.ctg010154l,s9125.ctg010715l,s9239.ctg010854l	102685,44201,31346,53648,88867,239371,76602,113883,294074,74314,122067,79729,53058,48714,56508,41110,32310,117274,43887,25455,29076,35822,53009,170132,66478,45575,47105,28113,76722,35493,69506,45179,19084,32974,54962,34658,66638,40490,24851,41616,50896,67429,85077,40156,32077,38096,68220,31883,36764,43378,43374,34806,25786,29652	2.66027,2.05158,3.48612,3.02043,3.12733,2.98045,3.19972,2.46176,3.6526,3.46753,3.25859,2.44872,2.795,2.36245,3.24318,2.54128,1.9144,3.10823,2.22903,3.11907,2.7859,1.84876,3.01754,3.69201,2.05364,3.84955,2.33954,1.81776,3.13505,2.03506,3.94485,2.33427,2.60125,2.69598,2.9206,1.7939,2.68378,2.31683,2.38529,3.6971,1.9246,2.63253,3.65234,1.53929,2.29677,2.90104,2.81434,2.15196,4.71861,2.77818,2.14464,2.17137,2.58258,2.46638	2.7	Fail	Neural Network (Specific Model)	11	0.856	69506	249.8744	3384180	0.45	3885	None	bin.113
MAG283	56.62	1.45	32	s71.ctg000106l,s297.ctg000481l,s468.ctg000733l,s591.ctg000918l,s601.ctg000932l,s1127.ctg001649l,s1291.ctg001863l,s1398.ctg001994l,s1763.ctg002437l,s1795.ctg002473l,s1900.ctg002597l,s2132.ctg002881l,s2414.ctg003200l,s2967.ctg003835l,s3209.ctg004106l,s3384.ctg004301l,s3851.ctg004826l,s4036.ctg005041l,s4167.ctg005189l,s4382.ctg005422l,s4386.ctg005426l,s5874.ctg007056l,s5993.ctg007181l,s6367.ctg007601l,s6719.ctg008001l,s6775.ctg008062l,s7016.ctg008322l,s7145.ctg008465l,s7324.ctg008659l,s7421.ctg008768l,s9469.ctg011135l,s9612.ctg011339l	58018,118352,84680,223914,37746,78527,70835,76947,78331,36074,55438,65118,50965,42897,19532,59329,72059,60809,51070,44750,128297,22297,36529,25501,25772,33555,37623,60248,53627,44575,29903,44251	3.04953,2.94177,2.22561,3.49207,2.28221,2.45238,3.59322,3.35385,3.09373,2.62835,1.93543,2.8621,2.59644,2.85744,1.87741,2.45374,3.98449,2.00183,3.94859,2.65226,2.86637,3.28726,2.70186,2.33671,2.03001,2.48978,2.34403,2.94293,2.9845,2.80662,2.10392,3.39879	2.7	Fail	Gradient Boost (General Model)	11	0.874	65118	258.5048	1927569	0.46	2183	None	bin.106
MAG284	69.49	0.87	23	s594.ctg000922l,s654.ctg001010l,s1331.ctg001914l,s1635.ctg002283l,s1805.ctg002485l,s2271.ctg003037l,s2741.ctg003580l,s3509.ctg004438l,s3510.ctg004439l,s3642.ctg004588l,s3838.ctg004810l,s4114.ctg005128l,s4567.ctg005628l,s4739.ctg005816l,s5636.ctg006799l,s6193.ctg007405l,s6492.ctg007738l,s6916.ctg008212l,s7203.ctg008529l,s7293.ctg008626l,s7389.ctg008730l,s7633.ctg009013l,s8187.ctg009631l	152220,62088,52759,79996,154633,92951,62544,110162,33123,59839,29079,26985,27867,52364,53974,38567,40032,17563,43158,76273,35506,38238,32461	3.6002,1.907,3.1008,3.60668,2.41622,2.97004,3.39991,3.00869,2.78952,2.32018,2.40748,1.77473,2.02854,3.01726,2.99758,2.62168,2.80049,2.87377,1.95545,3.05034,2.04791,2.69145,3.66463	2.7	Fail	Gradient Boost (General Model)	11	0.844	62544	246.1912	1372382	0.52	1574	None	bin.101
MAG285	53.42	4.73	19	s69.ctg000104l,s1196.ctg001744c,s1384.ctg001979l,s2166.ctg002918l,s2239.ctg003001l,s2939.ctg003802l,s4986.ctg006079l,s4988.ctg006081l,s5039.ctg006144l,s5847.ctg007029l,s6127.ctg007329l,s6886.ctg008179l,s7167.ctg008489l,s7176.ctg008499l,s7474.ctg008827l,s7741.ctg009136l,s7744.ctg009139l,s9006.ctg010569l,s9541.ctg011244l	38777,29777,36959,143092,127845,40674,56090,30495,33059,35740,43523,70184,15363,40259,49761,34159,34851,24040,8896	1.86854,10.2982,1.56342,2.61875,4.91604,1.29856,1.82782,1.86067,1.31551,1.68013,2.6692,3.04491,1.47321,2.29392,2.70553,1.17254,2.09423,2.29397,1.33833	2.5	Fail	Gradient Boost (General Model)	11	0.793	49761	229.4613	893544	0.29	1034	None	bin.916_sub
MAG286	52.52	0.36	34	s54.ctg000076l,s686.ctg001058l,s1240.ctg001797l,s1749.ctg002422l,s1779.ctg002453l,s1792.ctg002469l,s2011.ctg002730l,s2261.ctg003026l,s2303.ctg003074l,s2558.ctg003366l,s2873.ctg003732l,s3023.ctg003895l,s3568.ctg004504l,s4021.ctg005025l,s4277.ctg005306l,s4429.ctg005476l,s4486.ctg005540l,s4522.ctg005580l,s5144.ctg006256l,s5222.ctg006349l,s5347.ctg006482l,s5429.ctg006570l,s5979.ctg007166l,s5997.ctg007187l,s6149.ctg007352l,s6372.ctg007606l,s6469.ctg007712l,s6637.ctg007909l,s6852.ctg008144l,s6974.ctg008274l,s7063.ctg008373l,s7113.ctg008430l,s8336.ctg009801l,s8898.ctg010444l	40089,50954,18318,61611,68527,30285,34600,27864,41978,142947,108181,64274,25583,17331,70800,39824,129257,91565,80806,56540,55796,28438,45447,80547,24579,45062,36292,27808,47821,32638,66545,33614,49283,50689	2.17579,2.18314,2.00826,2.40043,1.96298,2.85104,2.8816,1.81064,2.62767,2.50416,2.23891,3.16722,1.39154,2.7446,2.97346,2.18891,3.26103,2.79325,2.09322,3.05013,2.23414,1.70793,2.88986,2.2408,2.45086,2.98967,2.80012,3.58714,2.9228,2.50754,2.05564,1.83947,3.65952,2.00461	2.5	Fail	Neural Network (Specific Model)	11	0.884	61611	241.7288	1825893	0.47	2242	None	bin.115
MAG287	33.86	0.46	28	s77.ctg000117l,s282.ctg000461l,s1031.ctg001529l,s1162.ctg001695l,s1771.ctg002445l,s2028.ctg002751l,s2167.ctg002919l,s2370.ctg003155l,s2456.ctg003248l,s2527.ctg003329l,s3337.ctg004250l,s3606.ctg004546l,s3639.ctg004584l,s3712.ctg004666l,s3861.ctg004836l,s4194.ctg005219l,s4492.ctg005549l,s4883.ctg005965l,s5014.ctg006113l,s5304.ctg006437l,s5620.ctg006782l,s6004.ctg007195l,s6348.ctg007577l,s6484.ctg007727l,s7202.ctg008528l,s7378.ctg008719l,s8698.ctg010208l,s9129.ctg010721l	60903,25167,35142,32574,53685,27536,54510,26318,15585,77630,21039,31824,35786,75102,81194,21076,29546,18859,71940,21408,41963,54361,30697,27647,27956,63193,44764,50526	2.21001,2.21521,3.3546,3.80918,1.96965,2.67958,2.52982,2.393,2.08001,2.36298,2.41256,2.32023,2.24329,3.22332,2.64777,2.74563,3.80718,2.0775,2.833,1.82722,1.91782,2.29861,2.74017,2.93588,2.02147,3.70734,2.11241,2.34368	2.5	Fail	Neural Network (Specific Model)	11	0.804	53685	253.9300	1157931	0.43	1228	None	bin.271
MAG288	52.48	1.17	8	s705.ctg001082l,s1692.ctg002354l,s2378.ctg003163l,s3816.ctg004788l,s5132.ctg006243l,s5989.ctg007176l,s7081.ctg008395l,s8594.ctg010094l	126307,99800,156636,60387,32439,51411,86026,88676	2.12542,2.60128,2.57858,2.65511,2.73808,2.44309,2.83697,2.58235	2.5	Fail	Gradient Boost (General Model)	11	0.850	99800	221.1350	701682	0.27	904	None	bin.172
MAG289	53.26	4.18	39	s292.ctg000474l,s445.ctg000699l,s487.ctg000763l,s892.ctg001351l,s1355.ctg001943l,s1849.ctg002534l,s1883.ctg002575l,s2255.ctg003017l,s2775.ctg003619l,s3809.ctg004778l,s3995.ctg004993l,s4233.ctg005262l,s4828.ctg005905l,s4990.ctg006083l,s5731.ctg006902l,s5779.ctg006956l,s5809.ctg006988l,s5825.ctg007005l,s5932.ctg007116l,s5951.ctg007136l,s6669.ctg007944l,s6856.ctg008148l,s6912.ctg008208l,s6950.ctg008246l,s7092.ctg008407l,s7107.ctg008424l,s7141.ctg008461l,s7204.ctg008530l,s7485.ctg008841l,s8056.ctg009488l,s8208.ctg009654l,s8422.ctg009894l,s8530.ctg010015l,s8647.ctg010155l,s9181.ctg010785l,s9206.ctg010814l,s9259.ctg010878l,s9391.ctg011041l,s9636.ctg011375l	50540,108658,41208,174354,109943,75851,119740,121402,57311,96627,48325,79507,28587,29598,14316,35100,57057,25861,44756,109845,37175,143461,42329,28388,28500,42030,77035,42653,34643,25803,37991,35220,29238,42099,52885,37135,20645,33804,28469	1.42171,2.88666,1.35026,3.80696,3.07385,3.0645,2.7541,3.21077,4.35055,2.30805,2.35029,3.16911,2.68235,2.91514,3.63349,1.63205,2.85673,1.91062,2.7173,3.49139,2.78001,3.14178,1.98594,2.68054,1.92448,2.26683,2.79761,2.57801,1.39753,2.80985,2.39238,2.30105,1.7302,3.44239,1.41913,2.15552,1.67358,2.93531,1.08842	2.5	Fail	Neural Network (Specific Model)	11	0.828	77035	248.1097	2248089	0.61	2515	None	bin.158
MAG290	41.41	0.07	18	s333.ctg000530l,s510.ctg000793l,s1229.ctg001780l,s2442.ctg003233l,s2584.ctg003399l,s3242.ctg004142l,s3554.ctg004486l,s3571.ctg004507l,s4393.ctg005435l,s4807.ctg005884l,s4868.ctg005947l,s5277.ctg006410l,s5507.ctg006657l,s7162.ctg008484l,s7361.ctg008701l,s7800.ctg009200l,s8430.ctg009904l,s8949.ctg010500l	66808,25280,92011,67093,57044,94430,25086,34191,31284,41137,52390,74725,30177,40874,54048,66755,70297,37068	2.03726,1.63741,2.65362,2.97555,1.69452,2.90011,2.65395,2.82885,2.73993,1.70249,2.89747,2.8615,2.62004,2.37258,1.91875,2.91465,2.7131,1.3095	2.4	Fail	Neural Network (Specific Model)	11	0.863	66755	259.5593	960698	0.54	1071	None	bin.125
MAG291	60.74	1.37	35	s206.ctg000324l,s218.ctg000343l,s868.ctg001317l,s1415.ctg002016l,s2159.ctg002910l,s2275.ctg003042l,s2309.ctg003081l,s2313.ctg003086l,s2444.ctg003236l,s2757.ctg003599l,s2998.ctg003869l,s3334.ctg004247l,s3770.ctg004733l,s4010.ctg005011l,s4831.ctg005909l,s4959.ctg006048l,s4969.ctg006058l,s5195.ctg006320l,s5271.ctg006404l,s5447.ctg006589l,s5478.ctg006626l,s5662.ctg006829l,s5960.ctg007147l,s6113.ctg007313l,s6476.ctg007719l,s6584.ctg007849l,s6751.ctg008037l,s7277.ctg008610l,s7464.ctg008815l,s8003.ctg009432l,s8055.ctg009487l,s8086.ctg009523l,s8363.ctg009829l,s8405.ctg009877l,s9026.ctg010597l	33808,53990,70797,42515,40902,41038,107844,57281,53171,59831,61983,95085,79016,29553,91389,39970,27897,32738,39523,30922,34599,83691,26229,44673,49230,31006,35724,48413,37624,57693,34045,44416,35811,24814,43305	1.46233,1.95509,2.37887,2.79318,2.06915,1.74738,2.43553,2.09685,2.06258,2.67191,2.68247,3.05087,1.99369,1.59259,2.34836,1.94741,4.58954,3.2577,2.43339,3.12596,2.25766,3.15985,2.27681,1.76727,2.2915,2.97271,2.05299,2.33272,1.71967,1.92063,2.26485,2.44337,1.66597,2.55563,3.09192	2.3	Fail	Gradient Boost (General Model)	11	0.863	53171	238.6900	1720526	0.46	2084	None	bin.130
MAG292	31.68	1.39	24	s436.ctg000682l,s532.ctg000826l,s1515.ctg002141l,s2575.ctg003386l,s2851.ctg003708l,s4176.ctg005200l,s4368.ctg005405l,s4464.ctg005514l,s4804.ctg005881l,s4951.ctg006039l,s5371.ctg006506l,s5383.ctg006518l,s6406.ctg007644l,s6595.ctg007861l,s7312.ctg008646l,s7433.ctg008782l,s7832.ctg009233l,s7881.ctg009297l,s8026.ctg009456l,s8072.ctg009506l,s8115.ctg009553l,s8352.ctg009818l,s8619.ctg010124l,s8867.ctg010410l	47274,67824,25860,51834,55386,57802,30069,43921,72970,29050,42513,30907,41151,73682,42483,100795,35135,58262,41140,42504,47655,33745,35959,31237	1.62361,2.83296,4.63127,2.3254,2.93816,2.03108,3.32755,2.82201,1.84253,3.43291,1.35696,2.73079,1.88122,3.30105,1.22273,2.23201,1.41312,2.20455,2.01905,3.56139,1.90548,2.15553,1.85439,1.34539	2.3	Fail	Neural Network (Specific Model)	11	0.835	47655	225.0345	1139158	0.52	1420	None	bin.222
MAG293	24.69	3.00	34	s160.ctg000257l,s208.ctg000328l,s385.ctg000612l,s968.ctg001458l,s1147.ctg001678l,s1347.ctg001934l,s1647.ctg002299l,s1706.ctg002369l,s2907.ctg003768l,s3013.ctg003884l,s3316.ctg004224l,s3492.ctg004420l,s3774.ctg004738l,s4407.ctg005452l,s4586.ctg005649l,s4719.ctg005793l,s5011.ctg006109l,s5281.ctg006414l,s5591.ctg006749l,s6186.ctg007397l,s6504.ctg007750l,s7130.ctg008449l,s7246.ctg008577l,s7363.ctg008703l,s7483.ctg008837l,s7563.ctg008930l,s7680.ctg009069l,s8191.ctg009635l,s8256.ctg009711l,s8453.ctg009929l,s8693.ctg010202l,s9152.ctg010753l,s9210.ctg010818l,s9675.ctg011436l	47797,121352,22743,43079,34901,43570,36844,44043,30559,21129,74633,25185,27423,27968,38593,28212,22672,48915,43027,31341,20660,34545,64853,44353,24357,22007,35529,69979,19144,26141,20968,23833,26288,11549	2.0481,3.58259,2.39348,1.91477,1.93851,1.43625,2.06524,2.02953,3.73945,1.31093,1.70395,2.78722,1.498,1.84751,1.73212,1.39726,2.77231,2.38232,2.35648,1.75281,1.63003,1.58936,3.33283,3.22012,3.19408,1.93201,1.80251,2.53993,2.63246,3.13274,1.80041,1.694,1.85818,7.29599	2.3	Fail	Neural Network (Specific Model)	11	0.820	43027	219.5929	1258192	0.58	1577	None	bin.859
MAG294	46.44	0.12	17	s449.ctg000704l,s1044.ctg001545l,s1277.ctg001842l,s1495.ctg002119l,s1852.ctg002537l,s2491.ctg003287l,s2713.ctg003549l,s2805.ctg003655l,s3440.ctg004365l,s3936.ctg004924l,s4991.ctg006084l,s5495.ctg006644l,s6600.ctg007866l,s7302.ctg008635l,s7422.ctg008769l,s7445.ctg008795l,s9652.ctg011396l	35400,45866,70877,51998,23546,33549,50473,36255,41690,28349,21692,44937,37327,46376,44368,27040,43010	1.14539,2.23532,1.7718,1.58104,2.19649,2.19498,1.85347,2.17842,2.50924,2.14419,2.36023,3.2246,2.86021,2.02005,2.58831,3.79874,1.24501	2.2	Fail	Gradient Boost (General Model)	11	0.821	44368	231.9370	682753	0.31	810	None	bin.203
MAG295	62.52	1.24	16	s539.ctg000838l,s628.ctg000965l,s1239.ctg001796l,s2941.ctg003805l,s3728.ctg004684l,s3749.ctg004708l,s3981.ctg004977l,s4487.ctg005541l,s5194.ctg006319l,s5818.ctg006998l,s6392.ctg007627l,s7083.ctg008397l,s7399.ctg008742l,s7851.ctg009259l,s8002.ctg009430l,s9396.ctg011047l	86049,54187,50726,31665,40307,64280,86797,29374,117106,36518,27419,31825,23236,91629,48382,36409	1.95599,2.53508,1.53964,1.45642,1.70608,2.44879,2.61362,2.2694,2.24477,2.05557,2.55356,2.46106,2.28801,1.7457,2.73785,1.48449	2.1	Fail	Gradient Boost (General Model)	11	0.788	64280	211.4490	855909	0.27	1069	None	bin.136
MAG296	43.50	0.88	29	s484.ctg000758l,s856.ctg001301l,s1370.ctg001963l,s1673.ctg002329l,s2999.ctg003870l,s3825.ctg004797l,s4329.ctg005362l,s4822.ctg005899l,s5170.ctg006291l,s5491.ctg006640l,s5840.ctg007022l,s6682.ctg007960l,s6840.ctg008131l,s6972.ctg008272l,s7565.ctg008932l,s7825.ctg009226l,s7883.ctg009300l,s7918.ctg009338l,s7990.ctg009417l,s8291.ctg009753l,s8534.ctg010020l,s8632.ctg010139l,s8657.ctg010165l,s8828.ctg010365l,s9025.ctg010596l,s9041.ctg010615l,s9077.ctg010659l,s9101.ctg010688l,s9131.ctg010723l	61865,35417,43827,43222,20482,67957,102725,19973,38243,111564,54733,61500,38532,55145,34692,41440,29371,57537,26158,29394,56552,40733,52863,41946,32489,17046,33742,39512,76128	2.4485,1.51856,2.74907,2.21873,2.15208,2.74181,3.02674,2.23089,1.71349,2.29187,1.8627,2.29711,3.1082,1.69661,2.24923,1.82327,1.86469,2.38983,1.41629,1.75003,2.68911,1.62319,2.18462,1.27694,1.85612,3.05392,1.39661,2.05112,2.76189	2.1	Fail	Gradient Boost (General Model)	11	0.865	54733	245.6398	1364788	0.42	1613	None	bin.171
MAG297	41.83	0.02	32	s607.ctg000939l,s755.ctg001155l,s1445.ctg002053l,s1931.ctg002632l,s2111.ctg002855l,s2154.ctg002905l,s2196.ctg002949l,s2373.ctg003158l,s2381.ctg003166l,s2703.ctg003539l,s3303.ctg004207l,s3304.ctg004210l,s3326.ctg004238l,s3500.ctg004429l,s3605.ctg004545l,s4355.ctg005390l,s4826.ctg005903l,s5319.ctg006453l,s5878.ctg007060l,s5986.ctg007173l,s6106.ctg007306l,s6211.ctg007424l,s6249.ctg007465l,s6409.ctg007647l,s6658.ctg007931l,s7334.ctg008671l,s8042.ctg009473l,s8302.ctg009764l,s8355.ctg009821l,s8371.ctg009837l,s8374.ctg009840l,s8893.ctg010439l	50689,56090,26059,55205,44395,37326,51826,38714,79344,28813,44454,91186,46244,51669,35868,49379,31723,62848,30590,45358,27990,43610,47461,63171,35986,29765,23551,42887,35064,39732,23489,18134	2.00942,2.91425,3.02574,2.1359,1.88751,1.2047,2.89012,2.37398,2.0938,1.44667,2.74409,3.05292,1.9468,2.07956,2.02259,1.63359,1.93779,1.88358,2.99777,2.22224,2.86825,2.38415,1.98789,2.31615,1.75098,2.23336,1.54852,2.1692,1.9182,2.38368,1.9569,1.81472	2.1	Fail	Neural Network (Specific Model)	11	0.823	46244	226.5423	1388620	0.57	1691	None	bin.175
MAG298	20.02	0.00	20	s122.ctg000181l,s572.ctg000887l,s1289.ctg001859l,s1548.ctg002185l,s2240.ctg003002l,s4048.ctg005055l,s4362.ctg005398l,s4441.ctg005489l,s4925.ctg006008l,s5354.ctg006489l,s6294.ctg007515l,s6333.ctg007559l,s6338.ctg007565l,s6820.ctg008110l,s7144.ctg008464l,s7559.ctg008926l,s7820.ctg009221l,s7856.ctg009264l,s9022.ctg010593l,s9269.ctg010888l	32559,34917,39285,50397,20606,68749,25096,32494,22172,35670,75608,19756,38775,29766,41180,65448,16728,28732,16510,31857	3.1602,2.25645,2.17041,1.68038,1.50533,2.01653,1.55332,1.90932,1.54959,2.09352,2.26004,3.29216,1.9948,1.92953,2.59337,1.99259,2.10206,2.79302,1.64762,2.44167	2.1	Fail	Neural Network (Specific Model)	11	0.821	38775	261.5890	726305	0.65	764	None	bin.219
MAG299	37.88	1.05	31	s2.ctg000004l,s1341.ctg001925l,s1343.ctg001927l,s1425.ctg002030l,s1542.ctg002173l,s2083.ctg002821l,s2269.ctg003035l,s2346.ctg003125l,s2747.ctg003589l,s3165.ctg004059l,s3823.ctg004795l,s4276.ctg005305l,s5107.ctg006218l,s5555.ctg006708l,s5639.ctg006802l,s5887.ctg007069l,s5965.ctg007152l,s6215.ctg007428l,s6420.ctg007661l,s6656.ctg007929l,s7125.ctg008444l,s7300.ctg008633l,s7330.ctg008667l,s7507.ctg008865l,s7988.ctg009415l,s8068.ctg009500l,s8123.ctg009561l,s8524.ctg010009l,s9136.ctg010729l,s9406.ctg011062l,s9699.ctg011466l	17335,124864,24967,62319,26416,22265,43387,29753,29885,34067,18971,38684,46163,35760,60185,22430,33493,31357,34993,33630,34208,56092,59009,56573,27668,56781,25532,59966,20362,26473,30133	3.04917,2.30214,1.85784,2.4676,2.02947,3.10721,1.87467,1.76911,1.48159,1.82083,1.69848,1.62724,2.00539,1.44962,1.739,1.76145,3.68989,1.56144,2.33568,1.82216,1.21187,2.11367,2.08583,2.42015,1.97987,1.89555,2.11173,2.18154,1.77785,1.87543,2.99356	2.0	Fail	Neural Network (Specific Model)	11	0.823	43387	214.5755	1223721	0.58	1576	None	bin.213
MAG300	16.13	0.03	14	s1860.ctg002547l,s2393.ctg003179l,s2436.ctg003226l,s3938.ctg004927l,s3963.ctg004955l,s5006.ctg006102l,s5284.ctg006417l,s5937.ctg007121l,s6090.ctg007288l,s6502.ctg007748l,s6596.ctg007862l,s7451.ctg008802l,s7824.ctg009225l,s7999.ctg009427l	31128,27286,29684,59200,36381,50425,27244,32321,70747,47619,89439,47361,30079,24737	2.04739,1.29286,1.58705,2.31439,1.79368,1.61265,2.66919,2.30319,1.79506,1.99581,2.58876,1.89015,1.87958,2.78224	2.0	Fail	Neural Network (Specific Model)	11	0.835	47619	225.2663	603651	0.59	751	None	bin.279
MAG301	24.76	0.00	23	s152.ctg000241l,s622.ctg000956l,s735.ctg001123l,s1559.ctg002197l,s1933.ctg002634l,s2929.ctg003792l,s3178.ctg004073l,s3310.ctg004218l,s4334.ctg005367l,s4613.ctg005677l,s4742.ctg005819l,s6016.ctg007210l,s6434.ctg007675l,s6518.ctg007767l,s6551.ctg007810l,s7155.ctg008477l,s7457.ctg008808l,s7713.ctg009107l,s7714.ctg009108l,s8170.ctg009612l,s8654.ctg010162l,s8936.ctg010487l,s9367.ctg011012l	54420,33754,22814,24783,45632,65610,37199,41119,37638,88751,35428,25011,36226,30107,26737,43510,17478,27885,36230,27857,42688,41173,34187	2.97181,1.59023,1.95424,1.55008,1.86623,1.82621,1.83846,3.0856,1.75872,2.17526,2.06134,3.12916,2.48312,1.63311,1.62264,2.46492,2.53942,1.56524,1.87165,2.55585,1.82653,1.47832,2.08579	2.0	Fail	Neural Network (Specific Model)	11	0.845	37638	260.7826	876237	0.55	952	None	bin.205
MAG302	28.31	3.70	31	s296.ctg000479l,s759.ctg001162l,s893.ctg001352l,s1180.ctg001720l,s1778.ctg002452l,s3520.ctg004450l,s3812.ctg004781l,s4359.ctg005394l,s4908.ctg005991l,s5562.ctg006717l,s5627.ctg006790l,s5859.ctg007041l,s6197.ctg007409l,s6481.ctg007724l,s7289.ctg008622l,s7415.ctg008760l,s7477.ctg008830l,s7603.ctg008974l,s8165.ctg009607l,s8237.ctg009689l,s8503.ctg009983l,s8880.ctg010424l,s9094.ctg010680l,s9108.ctg010695l,s9127.ctg010718l,s9150.ctg010750l,s9238.ctg010852l,s9403.ctg011059l,s9495.ctg011172l,s9549.ctg011252l,s9648.ctg011390l	43839,38543,28107,37268,19268,19009,42898,60555,60311,32209,31593,44429,31524,30404,21866,34832,36972,40345,27959,41590,34580,31097,44099,40251,20405,32047,23864,30080,32527,34121,24100	1.8926,1.18371,2.10473,1.49265,2.24385,1.52824,2.09434,1.41531,2.51083,1.72323,2.6832,2.31837,1.68461,1.41704,1.88529,2.19673,1.50133,1.5737,3.33468,1.63822,1.91438,1.36747,1.55337,2.16129,1.75882,2.40104,1.63363,1.89906,2.2894,1.55715,2.26864	1.9	Fail	Neural Network (Specific Model)	11	0.836	34832	229.9211	1070692	0.44	1305	None	bin.235
MAG303	16.93	0.07	10	s586.ctg000908l,s1212.ctg001761l,s2371.ctg003156l,s4541.ctg005601l,s7450.ctg008801l,s8164.ctg009606l,s8652.ctg010160l,s9004.ctg010566l,s9379.ctg011026l,s9689.ctg011454l	73707,29158,49355,42784,56278,35402,35887,33075,40805,21415	1.81159,1.40196,1.35773,1.80398,1.43383,1.6765,1.7591,1.62223,2.13698,2.01547	1.7	Fail	Neural Network (Specific Model)	11	0.874	42784	249.1141	417866	0.38	491	None	metabat2_bins.602