{"id":"W4413288733","doi":"10.1038/s41746-025-01941-3","title":"Incorporating large language models as clinical decision support in oncology: the Woollie model","year":2025,"lang":"en","type":"editorial","venue":"npj Digital Medicine","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Clinical decision making; Medicine; Oncology; Internal medicine; Computer science; Medical physics; Intensive care medicine","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":[0.01226666,0.001497797,0.001258583,0.002120303,0.0008947789,0.005098916,0.002521256,0.009724833,0.00380504],"category_scores_gemma":[0.0459007,0.0007276498,0.001474912,0.000983425,0.004252739,0.005983997,0.001486283,0.01618614,0.003555307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002357892,"about_ca_system_score_gemma":0.002460631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002554951,"about_ca_topic_score_gemma":0.003967091,"domain_scores_codex":[0.9957546,0.002244634,0.00038828,0.0004162831,0.001109981,0.00008619689],"domain_scores_gemma":[0.9437935,0.04887549,0.0007672236,0.000836622,0.004631882,0.001095249],"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":[0.00007548425,0.00001471084,0.0000924155,0.0005757982,0.00009285776,0.0002078631,0.00009530973,0.001167519,0.00008841903,0.0216866,0.9313777,0.04452537],"study_design_scores_gemma":[0.00007060515,0.0000424433,0.0001504289,0.001230627,0.0001294801,0.0003980806,0.00005377651,0.006316189,0.0002175624,0.052039,0.9392907,0.00006113596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0003255236,0.08985406,0.0200861,0.3310767,0.553008,0.00004768722,0.0002914544,0.000388294,0.004922188],"genre_scores_gemma":[0.007334474,0.06655265,0.007579653,0.07217541,0.8335886,0.00009887417,0.0001347142,0.0002893626,0.01224623],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01226666,"threshold_uncertainty_score":0.0648731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981051197987185,"score_gpt":0.4024374962192621,"score_spread":0.3826269842393902,"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."}}