{"id":"W4293023535","doi":"10.1177/08465371221121074","title":"Classification of Musculoskeletal Radiograph Requisition Appropriateness Using Machine Learning","year":2022,"lang":"en","type":"article","venue":"Canadian Association of Radiologists Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McMaster University","funders":"","keywords":"Medicine; Requisition; Appropriateness criteria; Radiography; Appropriate Use Criteria; Medical physics; Radiology; Artificial intelligence; Physical therapy; Internal 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":[0.003313777,0.0004878088,0.0005447041,0.003346099,0.0003286425,0.00100485,0.0005930736,0.0007681319,0.001113534],"category_scores_gemma":[0.02266102,0.0001629959,0.0004540568,0.001189452,0.0004082106,0.0007263502,0.000452785,0.0004686507,0.0005909678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007479692,"about_ca_system_score_gemma":0.001172202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003198777,"about_ca_topic_score_gemma":0.004089627,"domain_scores_codex":[0.9968168,0.001097324,0.0005927173,0.0004384517,0.0008928941,0.0001618558],"domain_scores_gemma":[0.983375,0.0109606,0.00254834,0.000404402,0.002484687,0.0002271722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001473215,0.0009572153,0.5210958,0.0009452415,0.0001804683,0.001188686,0.0007443991,0.02038836,0.02479257,0.0004710463,0.006478418,0.4212845],"study_design_scores_gemma":[0.0002052343,0.001254583,0.4162256,0.0004392594,0.0002026106,0.003336038,0.001144363,0.5460268,0.02329372,0.003316613,0.004425447,0.0001298636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9316633,0.0009416502,0.06133894,0.0008450717,0.0001027587,0.0004197639,0.0010296,0.001072228,0.002586729],"genre_scores_gemma":[0.9465316,0.0001480172,0.05138113,0.0001501617,0.00005685276,0.0001156276,0.00111635,0.00002318737,0.0004770251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003346099,"threshold_uncertainty_score":0.01752514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0924161225083393,"score_gpt":0.3661263185379593,"score_spread":0.27371019602962,"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."}}