{"id":"W4379521296","doi":"10.32920/23302229.v1","title":"Making up a Drug Epidemic: Constructing Drug Discourse during the Opioid Epidemic in Ontario","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Winnipeg; Centre for Social Innovation; York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Opioid epidemic; Deliberation; Opioid; Drug; Government (linguistics); Fentanyl; Political science; Medicine; Criminology; Sociology; Psychiatry; Politics; Pharmacology; Law","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01067877,0.000673291,0.0006890673,0.003226245,0.05326497,0.01379162,0.002360591,0.003544576,0.003451487],"category_scores_gemma":[0.01564813,0.0009517509,0.000485074,0.005353042,0.04301427,0.008334852,0.01174385,0.005675532,0.0002444315],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.2487519,"about_ca_system_score_gemma":0.1611462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.97503,"about_ca_topic_score_gemma":0.9852567,"domain_scores_codex":[0.9924014,0.003098417,0.0002757235,0.0005118006,0.001788727,0.001923909],"domain_scores_gemma":[0.9831241,0.009736247,0.001629938,0.0004956404,0.002514687,0.002499316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001988377,0.000008821192,0.002956594,0.00003390081,0.000002710662,0.0002984901,0.9844024,0.00005946885,0.0002042197,0.00930532,0.00110469,0.001603426],"study_design_scores_gemma":[0.000005524866,0.00000822131,0.005542469,0.00009219649,0.000008647189,0.00004169905,0.9433249,0.0002338004,0.0001731717,0.001867904,0.04867596,0.00002543727],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8793452,0.002272078,0.001596128,0.04324247,0.0002290956,0.0001412784,0.0002678448,0.00003328209,0.07287257],"genre_scores_gemma":[0.9878378,0.001432868,0.0007737431,0.001157308,0.0000436461,0.00005557864,0.0001015953,0.00004623327,0.008551252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.946735,"threshold_uncertainty_score":0.8713413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05989473490579234,"score_gpt":0.3478583701744142,"score_spread":0.2879636352686218,"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."}}