{"id":"W4396947711","doi":"10.1001/jamaoto.2024.1201","title":"Oropharyngeal Cancer Staging Health Record Extraction Using Artificial Intelligence","year":2024,"lang":"en","type":"article","venue":"JAMA Otolaryngology–Head & Neck Surgery","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Cancer staging; Stage (stratigraphy); Medicine; Cancer; Medical record; Distant metastasis; Retrospective cohort study; Documentation; TNM staging system; Artificial intelligence; Internal medicine; Oncology; Machine learning; Medical physics; Metastasis; Computer science; Staging system","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":[0.006160222,0.0007010391,0.0006978329,0.005805127,0.0004227569,0.001882816,0.001056608,0.0004321056,0.00142012],"category_scores_gemma":[0.02799518,0.0003259842,0.001277712,0.004694204,0.0002972038,0.001320297,0.001142301,0.0004966763,0.0006927566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001316532,"about_ca_system_score_gemma":0.002426174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01195631,"about_ca_topic_score_gemma":0.01160122,"domain_scores_codex":[0.9944818,0.001795501,0.001547419,0.001009571,0.001030555,0.0001351133],"domain_scores_gemma":[0.9829491,0.008649176,0.002465875,0.002652458,0.003096174,0.0001871767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006951455,0.0003943191,0.4244004,0.001268569,0.0007255049,0.0005144811,0.0009170803,0.03213598,0.006098126,0.00169526,0.01017595,0.520979],"study_design_scores_gemma":[0.0002831413,0.0007301228,0.3401612,0.000789046,0.0009535984,0.001590614,0.001193499,0.5972565,0.02344708,0.006694705,0.02671694,0.0001835193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5581422,0.002600061,0.3611817,0.002031047,0.0002091902,0.00411812,0.05723165,0.007421875,0.007064081],"genre_scores_gemma":[0.5887402,0.0006992022,0.3688584,0.0001783424,0.00007253369,0.0008167258,0.03963394,0.00006857005,0.0009322073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01195631,"threshold_uncertainty_score":0.03257871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09286949141705814,"score_gpt":0.3870921714391815,"score_spread":0.2942226800221233,"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."}}