{"id":"W6963027108","doi":"10.17615/pxed-wf87","title":"Sociodemographic and Clinical Predictors of Prescription Opioid Use in a Longitudinal Community-Based Cohort Study of Middle-Aged and Older Adults","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Economic Theory and Institutions","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; Centers for Disease Control and Prevention; Hamilton Health Sciences Foundation","keywords":"Depression (economics); Polypharmacy; Population; Logistic regression; Medical prescription; Cohort study; Cohort; Opioid; Prescription drug","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":[0.001088426,0.0002512654,0.0003271177,0.0006698214,0.0008129594,0.0006409398,0.0003974417,0.0005293417,0.001119343],"category_scores_gemma":[0.001765018,0.0003610569,0.0005675166,0.0009170696,0.0002062253,0.0005244621,0.000542822,0.0009527058,0.0002805152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003884755,"about_ca_system_score_gemma":0.0007435289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03896911,"about_ca_topic_score_gemma":0.0532825,"domain_scores_codex":[0.9995585,0.0001017917,0.00005141287,0.00008426297,0.0001050604,0.00009901258],"domain_scores_gemma":[0.9989733,0.0001022165,0.0003337843,0.00008473825,0.000194721,0.0003113037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003664157,0.00006351995,0.9994677,0.000002968852,0.00002732332,0.00002324353,0.00006071032,0.000006250616,0.00005361225,0.00000444597,0.00007721695,0.0001762988],"study_design_scores_gemma":[0.000005270529,0.00006148597,0.9995401,0.000004970321,0.00001587578,0.00004003098,0.0001940901,0.00005369908,0.000009333869,0.000004916399,0.00006859106,0.000001561926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986028,0.0001196812,0.00004858411,0.00007336633,0.000008735285,0.00002185522,0.0008516196,0.000002680332,0.0002706857],"genre_scores_gemma":[0.9987587,0.0001042758,0.00009665069,0.00007658353,0.000009221792,0.00003421341,0.0007110665,0.000001365481,0.0002079635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03896911,"threshold_uncertainty_score":0.07748455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08223688131448768,"score_gpt":0.235325610504918,"score_spread":0.1530887291904304,"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."}}