{"id":"W4412021516","doi":"10.1109/cbms65348.2025.00148","title":"Automated Digitisation and Analysis of Paper Pain Drawings for Improved Diagnostic Accuracy of Polymyalgia Rheumatica in Primary Care","year":2025,"lang":"en","type":"article","venue":"","topic":"Systemic Sclerosis and Related Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council Canada","keywords":"Polymyalgia rheumatica; Primary care; Computer science; Medicine; Artificial intelligence; Internal medicine; Family medicine; Giant cell arteritis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.002575534,0.000575399,0.0005163451,0.003610333,0.0003574593,0.001428166,0.000915213,0.0007522177,0.008163353],"category_scores_gemma":[0.01922234,0.0003532735,0.0004918524,0.002391423,0.0002087869,0.0006126247,0.0007440421,0.0005548854,0.003163527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005059061,"about_ca_system_score_gemma":0.0005628502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004971757,"about_ca_topic_score_gemma":0.00942713,"domain_scores_codex":[0.9978162,0.0009578718,0.0002461154,0.0004064872,0.0004567268,0.0001165407],"domain_scores_gemma":[0.9887476,0.005162627,0.001316631,0.001066134,0.003445252,0.0002617449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001192348,0.0004342973,0.2861584,0.0008883481,0.0001698502,0.0005435338,0.001015972,0.003948613,0.00956665,0.0006025322,0.02782702,0.6676523],"study_design_scores_gemma":[0.0003960933,0.00101425,0.7442484,0.0005620745,0.0002557357,0.001901438,0.002421856,0.2105974,0.01313692,0.003284194,0.0220256,0.0001560344],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8055986,0.0042297,0.1385102,0.004010172,0.0007014232,0.002142774,0.02332275,0.006969872,0.01451439],"genre_scores_gemma":[0.7650139,0.0013279,0.2244788,0.0004732176,0.0002812843,0.0006755074,0.005161724,0.000155276,0.002432364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008163353,"threshold_uncertainty_score":0.02730918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00610868975509521,"score_gpt":0.2571732297011284,"score_spread":0.2510645399460332,"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."}}