{"id":"W4406686499","doi":"10.23977/acss.2024.080709","title":"Advances in foundation models for genomics: A detailed exploration of developments","year":2024,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Yunnan Provincial Science and Technology Department; Yunnan University; Yunnan Normal University; National Natural Science Foundation of China","keywords":"Foundation (evidence); Genomics; Engineering ethics; Data science; Engineering; Computer science; Computational biology; Biology; Geography; Archaeology; Genome; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003828239,0.001271819,0.0009159711,0.001720061,0.0003616023,0.002532738,0.001462172,0.001259046,0.003201847],"category_scores_gemma":[0.007355057,0.0007512717,0.001135511,0.002078617,0.00127494,0.00551114,0.001765831,0.003956024,0.00164786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360461,"about_ca_system_score_gemma":0.001994196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00261021,"about_ca_topic_score_gemma":0.002474894,"domain_scores_codex":[0.9990981,0.0002904222,0.00005668591,0.0002137446,0.0002821232,0.00005895391],"domain_scores_gemma":[0.99714,0.002019602,0.0001096112,0.0002223748,0.0004255977,0.00008286628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008044932,0.00008701941,0.002123431,0.002715344,0.0001626624,0.0002372325,0.0003441911,0.0289585,0.003162232,0.3827809,0.02017202,0.559176],"study_design_scores_gemma":[0.00002057907,0.0001714065,0.001149213,0.002112421,0.0001507606,0.0006278704,0.0001902548,0.1391948,0.003719853,0.3746813,0.4778603,0.000121328],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.007893505,0.346983,0.6035025,0.01434059,0.0007702041,0.0001047307,0.0006755622,0.001016076,0.02471383],"genre_scores_gemma":[0.1133109,0.5438029,0.3278006,0.003615052,0.001633543,0.0002722301,0.001663912,0.0006221363,0.007278722],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003828239,"threshold_uncertainty_score":0.02024591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0367088778016446,"score_gpt":0.3171787022565989,"score_spread":0.2804698244549543,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}