{"id":"W4410203956","doi":"10.1371/journal.pdig.0000800","title":"Clinical insights: A comprehensive review of language models in medicine","year":2025,"lang":"en","type":"review","venue":"PLOS Digital Health","topic":"Topic Modeling","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Saint Mary's University","funders":"","keywords":"Computer science; Context (archaeology); Key (lock); Autonomy; Data science; Resource (disambiguation); Health care; Management science; Knowledge management; Artificial intelligence; Engineering","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":[0.005882959,0.001506649,0.002573979,0.005600622,0.0004500315,0.002608664,0.001853719,0.002089978,0.004777267],"category_scores_gemma":[0.01589105,0.0007660416,0.001588873,0.005008433,0.001451895,0.003612979,0.001824714,0.002752115,0.00176132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001559795,"about_ca_system_score_gemma":0.00450134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004063594,"about_ca_topic_score_gemma":0.005112851,"domain_scores_codex":[0.9983192,0.0008253616,0.0002810934,0.0001800355,0.0003444432,0.00004979649],"domain_scores_gemma":[0.9812317,0.01692968,0.0004979203,0.0002458886,0.0009439593,0.0001508455],"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":[0.00006609392,0.00005451639,0.0003690505,0.04511436,0.0003288013,0.0000959736,0.0002760761,0.0009416321,0.0002016607,0.01177506,0.01943546,0.9213414],"study_design_scores_gemma":[0.00003688555,0.0001580708,0.001669565,0.07073261,0.0009310521,0.001011813,0.0003499693,0.0009802385,0.0003779401,0.02123234,0.9024128,0.0001067468],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004781903,0.9979639,0.0005978909,0.0008157094,0.0001053979,0.000007001054,0.00002402639,0.000008368464,0.0004299356],"genre_scores_gemma":[0.00111086,0.9973007,0.0007770444,0.0003940031,0.0002534748,0.00001762051,0.00003685732,0.000005337949,0.0001041457],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005882959,"threshold_uncertainty_score":0.03111243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2057323525799405,"score_gpt":0.4502191212996913,"score_spread":0.2444867687197507,"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."}}