{"id":"W4407888374","doi":"10.1007/s12561-025-09475-8","title":"Introduction to Special Issue on Machine Learning in Biomedical Sciences","year":2025,"lang":"en","type":"article","venue":"Statistics in Biosciences","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biostatistics; Computer science; Data science; Artificial intelligence; Medicine; Public health; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004129413,0.002513093,0.003789662,0.005404288,0.001248182,0.005634122,0.001989264,0.003886538,0.07748808],"category_scores_gemma":[0.01510393,0.000722267,0.002403195,0.002748081,0.001396922,0.004389393,0.002229346,0.008583062,0.04944729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604211,"about_ca_system_score_gemma":0.002453016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009830788,"about_ca_topic_score_gemma":0.002660045,"domain_scores_codex":[0.9975103,0.0004556517,0.0003050606,0.0004779866,0.001084914,0.0001660817],"domain_scores_gemma":[0.9811218,0.008097616,0.0009342382,0.001003299,0.006152609,0.002690435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001681526,0.00002413242,0.00008081216,0.0002103626,0.00002026112,0.00002634682,0.00000613963,0.0001284229,0.0001048068,0.001336773,0.9760209,0.02202422],"study_design_scores_gemma":[0.0000177007,0.00005437635,0.0008353394,0.0003524125,0.00003011135,0.0001669378,0.00001415728,0.0008073291,0.0001054853,0.009646205,0.9879444,0.00002548457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001968753,0.03872912,0.008245626,0.04368299,0.8947577,0.00006178636,0.0006551638,0.0003932873,0.01327745],"genre_scores_gemma":[0.001049013,0.01742232,0.002054283,0.01656092,0.9194577,0.0000782411,0.0006130526,0.0005325088,0.04223197],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.07748808,"threshold_uncertainty_score":0.2592235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336694504180941,"score_gpt":0.3339881433114388,"score_spread":0.3206211982696294,"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."}}