{"id":"W2152161239","doi":"10.1200/jop.2013.001028","title":"Models That Work: Incorporating Quality Principles in Different Clinical Settings","year":2013,"lang":"en","type":"article","venue":"Journal of Oncology Practice","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Canadian Partnership Against Cancer; Cancer Care Ontario","funders":"","keywords":"Medicine; Quality (philosophy); Work (physics); MEDLINE; Data science; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01626975,0.0001853719,0.0009662586,0.0001873229,0.00005888569,0.00004922249,0.0001919355,0.0003097614,0.0001776128],"category_scores_gemma":[0.06298357,0.0001361978,0.0002392617,0.0002382894,0.0001296435,0.002163549,0.0001593812,0.002091171,0.00004764138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004535554,"about_ca_system_score_gemma":0.0008313141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001652187,"about_ca_topic_score_gemma":0.00004435281,"domain_scores_codex":[0.9922014,0.002363916,0.004232791,0.0002600141,0.0006478706,0.0002939331],"domain_scores_gemma":[0.9618636,0.02828278,0.007670924,0.0003626428,0.00144929,0.0003707163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0050594,0.00501052,0.6893458,0.00008497949,0.0004495411,0.0005710464,0.0008160112,0.0004300594,0.0004624967,0.0008457241,0.01415442,0.28277],"study_design_scores_gemma":[0.01169587,0.003388553,0.8967491,0.0002938268,0.0007285182,0.001749786,0.009485558,0.00280871,0.00007367065,0.003827716,0.06891601,0.0002826162],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8534266,0.0001066026,0.003080151,0.1381984,0.0006927595,0.0005125931,8.640714e-7,0.00001528951,0.003966786],"genre_scores_gemma":[0.9207545,0.0002666939,0.06578878,0.01222773,0.0008082736,0.00001222134,0.000004927509,0.00002147261,0.0001154162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2824874,"threshold_uncertainty_score":0.9449093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.582855420879729,"score_gpt":0.5880735195357244,"score_spread":0.005218098655995429,"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."}}