{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004200183,0.00009395311,0.0001650424,0.0001140996,0.0000216051,0.00005137283,0.00009932816,0.0000716106,6.4912e-7],"category_scores_gemma":[0.00001758375,0.00007988569,0.00002747829,0.00009219292,0.00004790958,0.00007862184,0.00005323977,0.00004021813,0.000001025476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001964144,"about_ca_system_score_gemma":0.00006799764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004734035,"about_ca_topic_score_gemma":0.00006320896,"domain_scores_codex":[0.9990391,0.00003600103,0.0004196079,0.0002124849,0.0001289848,0.0001638822],"domain_scores_gemma":[0.9996926,0.00005116732,0.0000610183,0.0000861175,0.00007118311,0.00003795112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001524833,0.00007857435,0.001114474,0.002682973,0.00003586972,0.000003079167,0.001244117,0.07152653,0.0184685,0.0009882725,0.00009603203,0.9036091],"study_design_scores_gemma":[0.0008108588,0.0004930804,0.00009427859,0.0005472929,0.000004807949,0.000004193048,0.0003109904,0.9348927,0.006766935,0.005239461,0.05060606,0.0002293793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05818005,0.02984513,0.9107603,0.00002836068,0.0004720627,0.0004999611,0.00001115071,0.000005432804,0.0001975114],"genre_scores_gemma":[0.9692873,0.02115473,0.009185524,0.0000199206,0.0001447885,0.00009204455,0.00007773175,0.00000843061,0.00002949119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9111073,"threshold_uncertainty_score":0.3257644,"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."}}