{"id":"W2789483059","doi":"10.1097/jom.0000000000001311","title":"Prescription Dispensing Patterns Before and After a Workers’ Compensation Claim","year":2018,"lang":"en","type":"article","venue":"Journal of Occupational and Environmental Medicine","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Toronto Public Health","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Medical prescription; Muscle relaxant; Nonsteroidal; Injury prevention; Poison control; Emergency medicine; Occupational safety and health; Anesthesia; Physical therapy; Internal medicine; Pharmacology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003699742,0.0001343755,0.000249004,0.001295181,0.0004113041,0.0005771116,0.0003593567,0.0004891754,0.001938779],"category_scores_gemma":[0.00203722,0.0001911621,0.0003086404,0.001221222,0.0002549498,0.0003503235,0.0003581149,0.0004270752,0.0003501422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000544,"about_ca_system_score_gemma":0.0007688907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1011521,"about_ca_topic_score_gemma":0.1401735,"domain_scores_codex":[0.9993296,0.00007821357,0.0001096197,0.0001257571,0.0002155554,0.000141403],"domain_scores_gemma":[0.9974632,0.0003640404,0.001499529,0.00006288413,0.0003504411,0.000259911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001201578,0.00004008273,0.997459,0.00001591157,0.00002330405,0.00006325745,0.0001399413,0.0000290487,0.0002799457,0.000005273347,0.0000751815,0.001748941],"study_design_scores_gemma":[0.000001549764,0.00003530413,0.9996071,0.000004597187,0.00000366838,0.00006322396,0.0001358427,0.00004210504,0.00004202592,0.000001583562,0.00006108802,0.000001879244],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984587,0.0001323808,0.00003327978,0.00002605067,0.000002335384,0.0000108291,0.0009442543,0.00000377681,0.0003883027],"genre_scores_gemma":[0.9985745,0.00008970604,0.00005184499,0.00002099323,0.000003253484,0.000008403446,0.0009053273,0.000002038423,0.0003439279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1011521,"threshold_uncertainty_score":0.2011267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545060808548829,"score_gpt":0.2709768189298092,"score_spread":0.2555262108443209,"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."}}