{"id":"W1550396361","doi":"10.1002/0470842555.ch30","title":"Evaluating and Improving Physician Prescribing","year":2000,"lang":"en","type":"other","venue":"Pharmacoepidemiology","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Pharmacoepidemiology; Medicine; Alternative medicine; Family medicine; Data science; Management science; Computer science; Medical prescription; Pharmacology; Engineering; Pathology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006671546,0.0003426367,0.0008759674,0.0001673449,0.00006101338,0.000009401915,0.0000971867,0.0002621975,0.003329215],"category_scores_gemma":[0.0004636775,0.0002855631,0.0001286331,0.00008235543,0.0001275136,0.00005875521,0.00009016632,0.0007883818,0.0001604306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002389768,"about_ca_system_score_gemma":0.00005294802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002066697,"about_ca_topic_score_gemma":0.000003491432,"domain_scores_codex":[0.9978573,0.0005074035,0.0004206191,0.0005682507,0.0001600771,0.0004863041],"domain_scores_gemma":[0.9982415,0.0008849883,0.0003505576,0.0002459349,0.00001275359,0.0002642541],"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":[0.0004986925,0.0001676106,0.01141279,0.001352941,0.000639856,0.00006991001,0.00008264613,0.00000919152,0.007882473,0.0001012943,0.4943484,0.4834342],"study_design_scores_gemma":[0.002044922,0.0002215391,0.0003654276,0.000283832,0.00102463,0.00006177654,0.000009778529,0.01794458,0.0001651716,0.00008160311,0.9774583,0.0003384122],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004283909,0.01604271,0.0001334276,0.002311788,0.0008859873,0.001332909,0.00004927982,0.0004350021,0.974525],"genre_scores_gemma":[0.05678105,0.01518942,0.01553123,0.09898267,0.009055323,0.0002606753,0.0004791306,0.002055453,0.8016651],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4831099,"threshold_uncertainty_score":0.9999596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2962103559069731,"score_gpt":0.5142947465678749,"score_spread":0.2180843906609017,"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."}}