Datasets:

TabBioMed
/

true_betalactamase_unique

row_idx int64	f_0_esm2_0 float32	f_1_esm2_1 float32	f_2_esm2_2 float32	f_3_esm2_3 float32	f_4_esm2_4 float32	f_5_esm2_5 float32	f_6_esm2_6 float32	f_7_esm2_7 float32	f_8_esm2_8 float32	f_9_esm2_9 float32	f_10_esm2_10 float32	f_11_esm2_11 float32	f_12_esm2_12 float32	f_13_esm2_13 float32	f_14_esm2_14 float32	f_15_esm2_15 float32	f_16_esm2_16 float32	f_17_esm2_17 float32	f_18_esm2_18 float32	f_19_esm2_19 float32	f_20_esm2_20 float32	f_21_esm2_21 float32	f_22_esm2_22 float32	f_23_esm2_23 float32	f_24_esm2_24 float32	f_25_esm2_25 float32	f_26_esm2_26 float32	f_27_esm2_27 float32	f_28_esm2_28 float32	f_29_esm2_29 float32	f_30_esm2_30 float32	f_31_esm2_31 float32	f_32_esm2_32 float32	f_33_esm2_33 float32	f_34_esm2_34 float32	f_35_esm2_35 float32	f_36_esm2_36 float32	f_37_esm2_37 float32	f_38_esm2_38 float32	f_39_esm2_39 float32	f_40_esm2_40 float32	f_41_esm2_41 float32	f_42_esm2_42 float32	f_43_esm2_43 float32	f_44_esm2_44 float32	f_45_esm2_45 float32	f_46_esm2_46 float32	f_47_esm2_47 float32	f_48_esm2_48 float32	f_49_esm2_49 float32	f_50_esm2_50 float32	f_51_esm2_51 float32	f_52_esm2_52 float32	f_53_esm2_53 float32	f_54_esm2_54 float32	f_55_esm2_55 float32	f_56_esm2_56 float32	f_57_esm2_57 float32	f_58_esm2_58 float32	f_59_esm2_59 float32	f_60_esm2_60 float32	f_61_esm2_61 float32	f_62_esm2_62 float32	f_63_esm2_63 float32	f_64_esm2_64 float32	f_65_esm2_65 float32	f_66_esm2_66 float32	f_67_esm2_67 float32	f_68_esm2_68 float32	f_69_esm2_69 float32	f_70_esm2_70 float32	f_71_esm2_71 float32	f_72_esm2_72 float32	f_73_esm2_73 float32	f_74_esm2_74 float32	f_75_esm2_75 float32	f_76_esm2_76 float32	f_77_esm2_77 float32	f_78_esm2_78 float32	f_79_esm2_79 float32	f_80_esm2_80 float32	f_81_esm2_81 float32	f_82_esm2_82 float32	f_83_esm2_83 float32	f_84_esm2_84 float32	f_85_esm2_85 float32	f_86_esm2_86 float32	f_87_esm2_87 float32	f_88_esm2_88 float32	f_89_esm2_89 float32	f_90_esm2_90 float32	f_91_esm2_91 float32	f_92_esm2_92 float32	f_93_esm2_93 float32	f_94_esm2_94 float32	f_95_esm2_95 float32	f_96_esm2_96 float32	f_97_esm2_97 float32	f_98_esm2_98 float32	f_99_esm2_99 float32	f_100_esm2_100 float32	f_101_esm2_101 float32	f_102_esm2_102 float32	f_103_esm2_103 float32	f_104_esm2_104 float32	f_105_esm2_105 float32	f_106_esm2_106 float32	f_107_esm2_107 float32	f_108_esm2_108 float32	f_109_esm2_109 float32	f_110_esm2_110 float32	f_111_esm2_111 float32	f_112_esm2_112 float32	f_113_esm2_113 float32	f_114_esm2_114 float32	f_115_esm2_115 float32	f_116_esm2_116 float32	f_117_esm2_117 float32	f_118_esm2_118 float32	f_119_esm2_119 float32	f_120_esm2_120 float32	f_121_esm2_121 float32	f_122_esm2_122 float32	f_123_esm2_123 float32	f_124_esm2_124 float32	f_125_esm2_125 float32	f_126_esm2_126 float32	f_127_esm2_127 float32	f_128_esm2_128 float32	f_129_esm2_129 float32	f_130_esm2_130 float32	f_131_esm2_131 float32	f_132_esm2_132 float32	f_133_esm2_133 float32	f_134_esm2_134 float32	f_135_esm2_135 float32	f_136_esm2_136 float32	f_137_esm2_137 float32	f_138_esm2_138 float32	f_139_esm2_139 float32	f_140_esm2_140 float32	f_141_esm2_141 float32	f_142_esm2_142 float32	f_143_esm2_143 float32	f_144_esm2_144 float32	f_145_esm2_145 float32	f_146_esm2_146 float32	f_147_esm2_147 float32	f_148_esm2_148 float32	f_149_esm2_149 float32	f_150_esm2_150 float32	f_151_esm2_151 float32	f_152_esm2_152 float32	f_153_esm2_153 float32	f_154_esm2_154 float32	f_155_esm2_155 float32	f_156_esm2_156 float32	f_157_esm2_157 float32	f_158_esm2_158 float32	f_159_esm2_159 float32	f_160_esm2_160 float32	f_161_esm2_161 float32	f_162_esm2_162 float32	f_163_esm2_163 float32	f_164_esm2_164 float32	f_165_esm2_165 float32	f_166_esm2_166 float32	f_167_esm2_167 float32	f_168_esm2_168 float32	f_169_esm2_169 float32	f_170_esm2_170 float32	f_171_esm2_171 float32	f_172_esm2_172 float32	f_173_esm2_173 float32	f_174_esm2_174 float32	f_175_esm2_175 float32	f_176_esm2_176 float32	f_177_esm2_177 float32	f_178_esm2_178 float32	f_179_esm2_179 float32	f_180_esm2_180 float32	f_181_esm2_181 float32	f_182_esm2_182 float32	f_183_esm2_183 float32	f_184_esm2_184 float32	f_185_esm2_185 float32	f_186_esm2_186 float32	f_187_esm2_187 float32	f_188_esm2_188 float32	f_189_esm2_189 float32	f_190_esm2_190 float32	f_191_esm2_191 float32	f_192_esm2_192 float32	f_193_esm2_193 float32	f_194_esm2_194 float32	f_195_esm2_195 float32	f_196_esm2_196 float32	f_197_esm2_197 float32	f_198_esm2_198 float32	f_199_esm2_199 float32	f_200_esm2_200 float32	f_201_esm2_201 float32	f_202_esm2_202 float32	f_203_esm2_203 float32	f_204_esm2_204 float32	f_205_esm2_205 float32	f_206_esm2_206 float32	f_207_esm2_207 float32	f_208_esm2_208 float32	f_209_esm2_209 float32	f_210_esm2_210 float32	f_211_esm2_211 float32	f_212_esm2_212 float32	f_213_esm2_213 float32	f_214_esm2_214 float32	f_215_esm2_215 float32	f_216_esm2_216 float32	f_217_esm2_217 float32	f_218_esm2_218 float32	f_219_esm2_219 float32	f_220_esm2_220 float32	f_221_esm2_221 float32	f_222_esm2_222 float32	f_223_esm2_223 float32	f_224_esm2_224 float32	f_225_esm2_225 float32	f_226_esm2_226 float32	f_227_esm2_227 float32	f_228_esm2_228 float32	f_229_esm2_229 float32	f_230_esm2_230 float32	f_231_esm2_231 float32	f_232_esm2_232 float32	f_233_esm2_233 float32	f_234_esm2_234 float32	f_235_esm2_235 float32	f_236_esm2_236 float32	f_237_esm2_237 float32	f_238_esm2_238 float32	f_239_esm2_239 float32	f_240_esm2_240 float32	f_241_esm2_241 float32	f_242_esm2_242 float32	f_243_esm2_243 float32	f_244_esm2_244 float32	f_245_esm2_245 float32	f_246_esm2_246 float32	f_247_esm2_247 float32	f_248_esm2_248 float32	f_249_esm2_249 float32	f_250_esm2_250 float32	f_251_esm2_251 float32	f_252_esm2_252 float32	f_253_esm2_253 float32	f_254_esm2_254 float32	f_255_esm2_255 float32	f_256_esm2_256 float32	f_257_esm2_257 float32	f_258_esm2_258 float32	f_259_esm2_259 float32	f_260_esm2_260 float32	f_261_esm2_261 float32	f_262_esm2_262 float32	f_263_esm2_263 float32	f_264_esm2_264 float32	f_265_esm2_265 float32	f_266_esm2_266 float32	f_267_esm2_267 float32	f_268_esm2_268 float32	f_269_esm2_269 float32	f_270_esm2_270 float32	f_271_esm2_271 float32	f_272_esm2_272 float32	f_273_esm2_273 float32	f_274_esm2_274 float32	f_275_esm2_275 float32	f_276_esm2_276 float32	f_277_esm2_277 float32	f_278_esm2_278 float32	f_279_esm2_279 float32	f_280_esm2_280 float32	f_281_esm2_281 float32	f_282_esm2_282 float32	f_283_esm2_283 float32	f_284_esm2_284 float32	f_285_esm2_285 float32	f_286_esm2_286 float32	f_287_esm2_287 float32	f_288_esm2_288 float32	f_289_esm2_289 float32	f_290_esm2_290 float32	f_291_esm2_291 float32	f_292_esm2_292 float32	f_293_esm2_293 float32	f_294_esm2_294 float32	f_295_esm2_295 float32	f_296_esm2_296 float32	f_297_esm2_297 float32	f_298_esm2_298 float32	f_299_esm2_299 float32	f_300_esm2_300 float32	f_301_esm2_301 float32	f_302_esm2_302 float32	f_303_esm2_303 float32	f_304_esm2_304 float32	f_305_esm2_305 float32	f_306_esm2_306 float32	f_307_esm2_307 float32	f_308_esm2_308 float32	f_309_esm2_309 float32	f_310_esm2_310 float32	f_311_esm2_311 float32	f_312_esm2_312 float32	f_313_esm2_313 float32	f_314_esm2_314 float32	f_315_esm2_315 float32	f_316_esm2_316 float32	f_317_esm2_317 float32	f_318_esm2_318 float32	f_319_esm2_319 float32	f_320_esm2_320 float32	f_321_esm2_321 float32	f_322_esm2_322 float32	f_323_esm2_323 float32	f_324_esm2_324 float32	f_325_esm2_325 float32	f_326_esm2_326 float32	f_327_esm2_327 float32	f_328_esm2_328 float32	f_329_esm2_329 float32	f_330_esm2_330 float32	f_331_esm2_331 float32	f_332_esm2_332 float32	f_333_esm2_333 float32	f_334_esm2_334 float32	f_335_esm2_335 float32	f_336_esm2_336 float32	f_337_esm2_337 float32	f_338_esm2_338 float32	f_339_esm2_339 float32	f_340_esm2_340 float32	f_341_esm2_341 float32	f_342_esm2_342 float32	f_343_esm2_343 float32	f_344_esm2_344 float32	f_345_esm2_345 float32	f_346_esm2_346 float32	f_347_esm2_347 float32	f_348_esm2_348 float32	f_349_esm2_349 float32	f_350_esm2_350 float32	f_351_esm2_351 float32	f_352_esm2_352 float32	f_353_esm2_353 float32	f_354_esm2_354 float32	f_355_esm2_355 float32	f_356_esm2_356 float32	f_357_esm2_357 float32	f_358_esm2_358 float32	f_359_esm2_359 float32	f_360_esm2_360 float32	f_361_esm2_361 float32	f_362_esm2_362 float32	f_363_esm2_363 float32	f_364_esm2_364 float32	f_365_esm2_365 float32	f_366_esm2_366 float32	f_367_esm2_367 float32	f_368_esm2_368 float32	f_369_esm2_369 float32	f_370_esm2_370 float32	f_371_esm2_371 float32	f_372_esm2_372 float32	f_373_esm2_373 float32	f_374_esm2_374 float32	f_375_esm2_375 float32	f_376_esm2_376 float32	f_377_esm2_377 float32	f_378_esm2_378 float32	f_379_esm2_379 float32	f_380_esm2_380 float32	f_381_esm2_381 float32	f_382_esm2_382 float32	f_383_esm2_383 float32	f_384_esm2_384 float32	f_385_esm2_385 float32	f_386_esm2_386 float32	f_387_esm2_387 float32	f_388_esm2_388 float32	f_389_esm2_389 float32	f_390_esm2_390 float32	f_391_esm2_391 float32	f_392_esm2_392 float32	f_393_esm2_393 float32	f_394_esm2_394 float32	f_395_esm2_395 float32	f_396_esm2_396 float32	f_397_esm2_397 float32	f_398_esm2_398 float32	f_399_esm2_399 float32	f_400_esm2_400 float32	f_401_esm2_401 float32	f_402_esm2_402 float32	f_403_esm2_403 float32	f_404_esm2_404 float32	f_405_esm2_405 float32	f_406_esm2_406 float32	f_407_esm2_407 float32	f_408_esm2_408 float32	f_409_esm2_409 float32	f_410_esm2_410 float32	f_411_esm2_411 float32	f_412_esm2_412 float32	f_413_esm2_413 float32	f_414_esm2_414 float32	f_415_esm2_415 float32	f_416_esm2_416 float32	f_417_esm2_417 float32	f_418_esm2_418 float32	f_419_esm2_419 float32	f_420_esm2_420 float32	f_421_esm2_421 float32	f_422_esm2_422 float32	f_423_esm2_423 float32	f_424_esm2_424 float32	f_425_esm2_425 float32	f_426_esm2_426 float32	f_427_esm2_427 float32	f_428_esm2_428 float32	f_429_esm2_429 float32	f_430_esm2_430 float32	f_431_esm2_431 float32	f_432_esm2_432 float32	f_433_esm2_433 float32	f_434_esm2_434 float32	f_435_esm2_435 float32	f_436_esm2_436 float32	f_437_esm2_437 float32	f_438_esm2_438 float32	f_439_esm2_439 float32	f_440_esm2_440 float32	f_441_esm2_441 float32	f_442_esm2_442 float32	f_443_esm2_443 float32	f_444_esm2_444 float32	f_445_esm2_445 float32	f_446_esm2_446 float32	f_447_esm2_447 float32	f_448_esm2_448 float32	f_449_esm2_449 float32	f_450_esm2_450 float32	f_451_esm2_451 float32	f_452_esm2_452 float32	f_453_esm2_453 float32	f_454_esm2_454 float32	f_455_esm2_455 float32	f_456_esm2_456 float32	f_457_esm2_457 float32	f_458_esm2_458 float32	f_459_esm2_459 float32	f_460_esm2_460 float32	f_461_esm2_461 float32	f_462_esm2_462 float32	f_463_esm2_463 float32	f_464_esm2_464 float32	f_465_esm2_465 float32	f_466_esm2_466 float32	f_467_esm2_467 float32	f_468_esm2_468 float32	f_469_esm2_469 float32	f_470_esm2_470 float32	f_471_esm2_471 float32	f_472_esm2_472 float32	f_473_esm2_473 float32	f_474_esm2_474 float32	f_475_esm2_475 float32	f_476_esm2_476 float32	f_477_esm2_477 float32	f_478_esm2_478 float32	f_479_esm2_479 float32	target float32
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2	0.012935	0.045637	0.029789	0.204186	-0.035178	-0.033379	-0.008756	0.034332	-0.074822	0.086559	-0.065431	-0.006492	-0.034833	0.03629	-0.143853	0.050183	0.042855	0.038807	-0.255554	-0.017095	0.097326	0.000772	0.062642	-0.052548	-0.14163	0.148066	0.221511	0.067087	-0.035139	0.010293	-0.122036	0.059637	0.116285	0.033049	0.080155	-0.02609	0.03286	-0.066018	-0.142312	0.03311	-0.03688	-0.024874	-0.026115	-0.161311	0.095986	0.272516	3.321599	0.112511	-0.128383	-0.001179	-0.065384	0.118038	-0.139449	-0.095527	0.163457	-0.022117	0.038672	-0.051246	0.086561	0.013952	0.070722	0.041589	0.283502	0.043951	-0.118663	-0.007184	0.229131	-0.006741	0.028013	0.021122	-0.101562	-0.025509	0.223545	0.042696	0.022647	0.15483	-0.140808	-0.120405	0.165932	0.089116	0.197249	0.088524	0.043004	-0.12828	-0.027359	-0.238431	0.097103	-0.004768	0.062291	0.166907	0.074153	-0.0489	-0.143409	0.072051	-0.041492	0.050626	0.120468	-0.008193	0.114345	0.015552	0.134247	-0.067078	0.082058	0.071122	0.084496	-0.059612	-0.083758	-0.00299	-0.064999	-0.156778	-0.076683	-0.160741	-0.081104	0.077854	-0.072944	-0.005135	0.033759	0.177806	0.075502	-0.084515	-0.062448	0.000465	0.146273	-0.096223	-0.280744	-0.058848	0.154405	-0.141846	0.148444	-0.084802	0.112016	0.148933	0.089371	0.052385	-0.172334	0.141665	0.136556	0.195157	0.070369	0.128083	0.104363	0.01903	-0.040162	0.03514	-0.012718	-0.044785	0.023185	0.05332	0.071821	0.024673	0.055198	-0.028443	-0.111289	0.049489	0.222329	-0.066788	-0.122297	-0.146955	0.177642	0.001673	-0.024386	-0.098127	0.033802	0.024193	-0.149557	-0.126118	0.068315	-0.356737	-0.111752	0.033611	-0.145647	0.166199	0.006101	0.033123	0.166039	0.058576	-0.003322	-0.195216	-0.072423	-0.023663	0.002781	-0.180462	-0.136478	-0.02538	-0.106477	-0.128943	-0.067788	0.230526	-0.132483	-0.063564	0.034384	-0.021132	0.066257	-0.003749	-0.002979	-0.040417	-0.278071	0.012572	0.002605	-0.116748	0.126282	0.023012	0.024632	-0.12722	0.034926	0.061505	-0.232594	0.031251	0.107925	0.005016	0.103475	0.122696	-0.12155	-0.014842	0.040812	-0.085233	0.011154	0.019943	0.031184	0.081669	-0.270677	-0.0217	0.098414	-0.026597	-0.068395	-0.172152	0.056461	-0.021854	0.126144	-0.05774	0.035226	-0.00756	-0.095082	0.116631	-0.183555	-0.109773	-0.02207	0.098565	0.054278	-0.065269	0.005255	0.007612	0.05399	-0.122769	0.024043	-0.143321	-0.021082	-0.149018	-0.140957	0.067473	0.066997	-0.059535	0.123874	0.048283	-0.075318	-0.080139	-0.193427	-0.022628	-0.101698	-0.18949	0.033902	0.020078	0.02428	-0.018823	-0.185435	0.047736	0.065586	0.173842	-0.188383	-0.079555	0.037417	-0.070742	-0.073134	0.054381	-0.045489	0.12586	-0.083543	0.016202	-0.131672	-0.139628	-0.171892	0.083138	-0.081254	-0.00001	-0.126234	-0.090916	-0.010791	0.107013	0.088827	-0.170587	0.06573	-0.149355	0.118082	-0.038343	0.065496	0.111367	0.019792	-0.120572	0.085801	-0.532264	-0.003094	-0.022495	0.103033	0.031396	-0.001134	-0.0101	0.069796	-0.087435	0.093879	-0.144681	-0.188541	0.010526	-0.028448	0.00397	0.076715	0.120893	0.188335	-0.02032	-0.08374	0.068142	0.086637	0.105812	-0.053314	0.039995	0.042684	-0.019707	0.150454	0.059519	-0.043316	0.075608	0.036239	0.174738	0.07823	-0.036055	0.077414	0.085016	0.155648	-0.047859	-0.03562	-0.081438	-0.144354	-0.027352	0.218816	0.005177	-0.076208	0.096685	0.084729	0.037517	0.474282	-0.11234	0.130391	0.073088	-0.014351	-0.057868	0.242542	-0.046248	-0.074003	0.067997	-0.075921	0.00452	0.097233	-0.010232	-0.015135	-0.187359	-0.006405	0.107434	-0.040138	0.148169	0.050584	0.206199	-0.068014	-0.157326	-0.116085	-0.008963	0.063041	-0.125555	0.010589	0.092527	-0.220596	0.051528	0.040927	0.056208	0.124788	0.133659	-0.0233	-0.005479	-0.199314	0.069526	0.062996	0.089313	0.065392	-0.068864	-0.064814	-0.036571	-0.113905	-0.043163	-0.041445	0.189753	-0.043101	-0.208181	0.073975	-0.125944	0.063466	-0.02777	-0.054138	0.096769	0.085413	-0.047287	0.12444	0.082564	-0.093544	-0.044965	-0.173174	-0.159057	-0.011045	0.051322	0.109431	-0.087624	-0.027619	-0.025772	-0.07942	0.270179	-0.139264	-0.020768	0.009563	0.102635	0.011443	0.162477	0.035819	0.080529	-0.000615	-0.055481	-0.04787	-0.144886	-0.147194	-0.022697	0.022262	0.029129	0.018956	-0.073047	0.093881	0.007629	-0.127942	0.027316	0.153068	0.2404	-0.143993	0.11258	-0.072803	0.051172	-0.011176	-0.163686	-0.010486	0.079867	-0.023541	0.193069	-0.150228	-0.300864	0.049443	-0.030272	-0.421695	-0.095483	-0.069741	-0.12001	0.146399	-0.166572	-0.123046	-0.107955	0.138122	0.129176	-0.013629	0.085878	-0.020829	0.099079	0.149673	0.004491	-0.006679	-0.078112	0.053851	-0.166001	0.040036
3	0.013857	0.041392	0.028246	0.211351	-0.03585	-0.032206	-0.008679	0.035654	-0.083186	0.084355	-0.072869	-0.008008	-0.029502	0.035514	-0.13944	0.05337	0.053098	0.037577	-0.254846	-0.010281	0.101382	0.001317	0.065038	-0.057654	-0.138083	0.144953	0.208372	0.067379	-0.036737	0.006076	-0.115357	0.061212	0.11605	0.03075	0.081885	-0.021582	0.03114	-0.070911	-0.148243	0.026818	-0.035357	-0.025645	-0.014877	-0.170911	0.093671	0.276791	3.267815	0.110472	-0.126346	0.001114	-0.06502	0.11728	-0.135303	-0.100817	0.165836	-0.023693	0.034892	-0.054384	0.078515	0.015245	0.060971	0.047062	0.281882	0.042888	-0.125088	-0.008572	0.228855	-0.011243	0.027593	0.020938	-0.105188	-0.029349	0.224117	0.047565	0.022056	0.152619	-0.137082	-0.127096	0.169335	0.087035	0.198086	0.084032	0.038749	-0.136667	-0.028343	-0.23815	0.101523	-0.009255	0.059196	0.165352	0.075938	-0.049323	-0.145257	0.066868	-0.040668	0.04768	0.113744	-0.005063	0.118283	0.0136	0.134332	-0.061739	0.081229	0.074882	0.073808	-0.05942	-0.085829	0.000252	-0.063997	-0.158872	-0.069336	-0.157969	-0.079759	0.085588	-0.066785	-0.007286	0.034854	0.172126	0.081939	-0.083883	-0.063481	-0.00318	0.152152	-0.100684	-0.28592	-0.061785	0.155338	-0.142935	0.149383	-0.079609	0.116643	0.152204	0.095352	0.057885	-0.166959	0.138685	0.137187	0.202615	0.067989	0.132548	0.102765	0.024589	-0.039235	0.03843	-0.013631	-0.045548	0.021643	0.05292	0.073725	0.021693	0.049489	-0.02572	-0.109575	0.055501	0.217247	-0.067948	-0.125923	-0.150187	0.172537	-0.001555	-0.027992	-0.092971	0.042084	0.023837	-0.150495	-0.117024	0.068201	-0.355408	-0.109829	0.033266	-0.151592	0.167097	0.004171	0.029076	0.18205	0.055003	0.00027	-0.192085	-0.067733	-0.026249	0.004294	-0.17098	-0.146236	-0.023337	-0.108233	-0.128686	-0.066604	0.230867	-0.134763	-0.070246	0.032915	-0.01362	0.065513	-0.003112	-0.005162	-0.042424	-0.279105	0.023976	-0.005708	-0.119494	0.133859	0.026116	0.026175	-0.134817	0.033394	0.065065	-0.2268	0.030374	0.106624	0.009527	0.107939	0.126259	-0.117951	-0.01433	0.041558	-0.085211	0.000053	0.017135	0.028261	0.088955	-0.272693	-0.024757	0.094998	-0.020987	-0.067139	-0.176529	0.05611	-0.021221	0.122002	-0.054432	0.037426	-0.006458	-0.088278	0.119359	-0.187937	-0.116661	-0.022927	0.101461	0.052059	-0.055504	0.005321	0.017829	0.061117	-0.125032	0.020387	-0.138439	-0.028014	-0.153416	-0.143442	0.052445	0.064408	-0.055407	0.124058	0.05748	-0.065971	-0.08704	-0.189511	-0.028603	-0.100953	-0.19229	0.032246	0.013909	0.028605	-0.026792	-0.191179	0.050777	0.061824	0.175253	-0.192854	-0.078892	0.039697	-0.071038	-0.083059	0.045835	-0.048779	0.132321	-0.089909	0.011339	-0.122607	-0.141342	-0.171563	0.086876	-0.085706	0.004384	-0.1222	-0.084373	-0.013275	0.103386	0.082703	-0.168979	0.065805	-0.151637	0.117807	-0.032977	0.063728	0.1036	0.020036	-0.119837	0.090475	-0.533558	-0.007529	-0.017518	0.105363	0.033895	-0.000102	-0.008709	0.071316	-0.095398	0.093151	-0.145432	-0.193874	0.006265	-0.027798	0.007285	0.080903	0.114554	0.193583	-0.02551	-0.084518	0.063448	0.084597	0.104572	-0.052213	0.045131	0.048434	-0.016763	0.152121	0.058667	-0.041978	0.069314	0.038846	0.181391	0.076867	-0.038573	0.086955	0.083169	0.162602	-0.037474	-0.040192	-0.079292	-0.134294	-0.023134	0.217231	0.0117	-0.076525	0.100401	0.086934	0.0382	0.484901	-0.112527	0.130893	0.078011	-0.015187	-0.058581	0.257243	-0.052343	-0.075229	0.065383	-0.074977	0.007829	0.097084	-0.016422	-0.005335	-0.178744	0.001065	0.10392	-0.032357	0.142084	0.047214	0.207537	-0.065264	-0.15888	-0.115683	-0.007365	0.05883	-0.127014	0.014436	0.089961	-0.216204	0.050208	0.042289	0.05807	0.11974	0.138999	-0.0296	0.003216	-0.204992	0.067639	0.060275	0.092317	0.056606	-0.067723	-0.070109	-0.042419	-0.11318	-0.052036	-0.041346	0.187955	-0.037726	-0.210697	0.073658	-0.124394	0.06574	-0.028294	-0.041819	0.094345	0.083585	-0.043904	0.12637	0.083592	-0.097375	-0.047803	-0.171716	-0.153251	-0.016485	0.055511	0.111192	-0.081877	-0.024141	-0.030678	-0.08557	0.262655	-0.138256	-0.022895	0.010034	0.101436	0.014297	0.166457	0.036258	0.087489	-0.003988	-0.052884	-0.045422	-0.14567	-0.147384	-0.012795	0.023191	0.027132	0.033653	-0.06918	0.096696	0.007544	-0.128016	0.029579	0.15059	0.24313	-0.146957	0.11305	-0.077295	0.049154	-0.011936	-0.162014	-0.01048	0.083904	-0.017833	0.185302	-0.154388	-0.309845	0.047488	-0.028672	-0.411224	-0.092322	-0.071715	-0.117986	0.145236	-0.172902	-0.128498	-0.099008	0.138003	0.128547	-0.010528	0.087859	-0.028861	0.101364	0.147684	0.005981	0.000259	-0.085425	0.052751	-0.171973	0.000832
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true_betalactamase_unique

Part of TabBioMed (TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning), a benchmark of 94 curated biomedical tabular datasets. Code, preprocessing and documentation: https://github.com/AI-sandbox/TabBioMed.

Sequence-level regression task predicting the fitness of all single codon substitutions in the TEM-1 Beta-lactamase gene. Labels measure the ability to confer ampicillin resistance. The Unique dataset contains a random maximal subset of non-degenerate coding sequences (one CDS per protein), using raw CDS fitness values. The source provides coding DNA sequences (CDS); they were translated with the standard genetic code before featurization, and nonsense mutants (CDS with a premature in-frame stop codon) were removed from all splits. Features: mean-pooled ESM-2 (esm2_t12_35M_UR50D) embeddings of the translated protein.

Domain	Task	Samples	Features	Classes
Proteomics	regression	5,128	480	-

Splits. Fixed train/val/test split (3271/832/1025 rows).

Files

data/**.parquet: one row per sample. row_idx is the row index in the original TabBioMed array; f_<i>[_<name>] are the features (in order); target (or target_<j> for multi-target tasks) is the label. Categorical feature indices (0-based, among the features): []. Missing values are stored as nulls.
metadata.json: TabBioMed task metadata (task type, categorical indices, source, description).
feature_names.json: original feature names, in column order.

from datasets import load_dataset
ds = load_dataset("TabBioMed/true_betalactamase_unique")

A Croissant (1.1) description with Responsible-AI fields is distributed with the TabBioMed release.

Source and license

Source: InstaDeepAI/true-cds-protein-tasks (Hugging Face). Original data from Firnberg et al. — systematic fitness landscape of all single codon mutations in the TEM-1 Beta-lactamase gene synthesized in E. coli. Fitness measured as a weighted average of allele counts over ampicillin-concentration plates, normalised by WT fitness.

This derived dataset is distributed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Please also cite and respect the terms of the original source.

Citation

@inproceedings{tabbiomed2026,
  title     = {TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning},
  author    = {Mateo Bernad{\'o}, Pau and Polapragada, Saivenkata Nagavyjayanthi and Bonet, David and Arbiol Rakuljic, Pol and Mogas Pladevall, Laia and Comajoan Cara, Mar{\c{c}}al and Gonzalez Ferrer, Jesus and Abante, Jordi and Mas Montserrat, Daniel and Haussler, David and Ioannidis, Alexander G.},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track},
  year      = {2026}
}

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