{"id":"W4416590420","doi":"10.2196/76326","title":"Large Language Models in Critical Care Medicine: Scoping Review","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; MEDLINE; Domain (mathematical analysis); Telehealth; Perspective (graphical)","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":[0.02653882,0.002074511,0.005903461,0.01874262,0.001222387,0.005582196,0.003406335,0.004160507,0.008705947],"category_scores_gemma":[0.1350327,0.001393321,0.008403682,0.01999625,0.001975219,0.005760836,0.00352934,0.003271777,0.001190498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005755756,"about_ca_system_score_gemma":0.02564689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132157,"about_ca_topic_score_gemma":0.01613878,"domain_scores_codex":[0.9816878,0.009146439,0.004993063,0.001062309,0.002750429,0.0003599194],"domain_scores_gemma":[0.8523475,0.1251371,0.01038968,0.00257752,0.008996951,0.0005511876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001438799,0.00005558918,0.0004952389,0.780606,0.003720402,0.0001779549,0.0006137154,0.001086762,0.0001214076,0.004374371,0.009138382,0.1994662],"study_design_scores_gemma":[0.0000561914,0.00008649097,0.0006489364,0.9265971,0.007912508,0.000215355,0.0003765482,0.0003920832,0.0001057515,0.003910405,0.05965532,0.00004327464],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002084625,0.9962294,0.001009859,0.0009674878,0.000211728,0.0003456544,0.000240035,0.00001922608,0.0007681659],"genre_scores_gemma":[0.004803342,0.9909748,0.001989382,0.000626502,0.0002083587,0.0009542155,0.0003006203,0.00001325747,0.0001295213],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02653882,"threshold_uncertainty_score":0.1403524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1289643715271696,"score_gpt":0.5330755488778534,"score_spread":0.4041111773506837,"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."}}