{"id":"W4405860078","doi":"10.5376/cmb.2024.14.0013","title":"AI in Biology: Transforming Genomic Research with Machine Learning","year":2024,"lang":"en","type":"article","venue":"Computational Molecular Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biology; Computational biology; Cognitive science; Evolutionary biology; Data science; Computer science; Psychology","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":[0.007501959,0.0008700047,0.0008780027,0.003332812,0.001066344,0.00672979,0.00208252,0.002325205,0.003221345],"category_scores_gemma":[0.01643249,0.0004820234,0.0008636971,0.002655937,0.01175459,0.009324405,0.004585635,0.005077601,0.001386384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002096866,"about_ca_system_score_gemma":0.002684113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001795602,"about_ca_topic_score_gemma":0.001125914,"domain_scores_codex":[0.9963044,0.001920396,0.0001618146,0.0005234319,0.0009446533,0.0001453162],"domain_scores_gemma":[0.9829113,0.01334771,0.0005195337,0.001895687,0.0009148673,0.0004109289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004286949,0.00009201419,0.002212472,0.0006053301,0.00008248964,0.0001361493,0.0008221845,0.009699872,0.0019473,0.7857763,0.008824304,0.1897587],"study_design_scores_gemma":[0.00001132839,0.00002260097,0.0005116655,0.0002302417,0.00001399136,0.00008398258,0.0002715234,0.01695626,0.0009002101,0.9373565,0.04361494,0.00002676328],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008835069,0.02745762,0.8399971,0.07156819,0.001598231,0.0001242795,0.0003285993,0.001434544,0.04865636],"genre_scores_gemma":[0.2322865,0.03497989,0.7099752,0.01056115,0.003878858,0.000333464,0.0005654718,0.0004964683,0.006922938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007501959,"threshold_uncertainty_score":0.03967464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02516239825888492,"score_gpt":0.3662489068911247,"score_spread":0.3410865086322398,"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."}}