{"id":"W4379966348","doi":"10.1111/add.16268","title":"Prevalence of opioid dependence in New South Wales, Australia, 2014–16: Indirect estimation from multiple data sources using a Bayesian approach","year":2023,"lang":"en","type":"article","venue":"Addiction","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"National Institute on Drug Abuse; National Health and Medical Research Council; National Institute for Health and Care Research; National Institute for Health Research Health Protection Research Unit; Fonds de Recherche du Québec - Santé; Medical Research Council; Department of Health and Aged Care, Australian Government; NIHR Bristol Biomedical Research Centre","keywords":"Medicine; Opioid; Adverse effect; Demography; Commonwealth; Population; Confidence interval; Cohort; Internal medicine; Emergency medicine; Environmental health; Geography","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":[0.0229285,0.0007389442,0.001134521,0.004045904,0.0006130566,0.001847999,0.001578376,0.0008207314,0.00127681],"category_scores_gemma":[0.07154107,0.00142095,0.002367285,0.002889547,0.0009896014,0.00170129,0.004295844,0.001491039,0.0003033734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003117083,"about_ca_system_score_gemma":0.003047992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1208543,"about_ca_topic_score_gemma":0.09713709,"domain_scores_codex":[0.9823819,0.01222013,0.001192703,0.001748279,0.002093125,0.0003638917],"domain_scores_gemma":[0.962994,0.01992505,0.01014319,0.001875331,0.004572923,0.000489431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001361827,0.0001253673,0.9435323,0.0006062103,0.001986617,0.0001373174,0.001385162,0.0176226,0.0002012594,0.002747823,0.0009945985,0.03052456],"study_design_scores_gemma":[0.0000829866,0.0003012461,0.8436094,0.001120646,0.001092044,0.0004224705,0.0008227552,0.1400318,0.0003201584,0.008522012,0.003580796,0.00009376507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8525869,0.00279683,0.1282336,0.001893045,0.00004895555,0.001158979,0.008364707,0.0001707684,0.004746227],"genre_scores_gemma":[0.9289632,0.001408228,0.06232483,0.0003915344,0.00005032976,0.001145566,0.004677579,0.00002281638,0.001015821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1208543,"threshold_uncertainty_score":0.2403018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0718104218660611,"score_gpt":0.313335529065114,"score_spread":0.2415251071990529,"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."}}