{"id":"W2733016345","doi":"10.35502/jcswb.42","title":"Learning from Ontario’s municipal drug strategies: an implementation framework for reducing harm through coordinated prevention, enforcement, treatment, and housing","year":2017,"lang":"en","type":"article","venue":"Journal of Community Safety and Well-Being","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Harm reduction; Enforcement; Thematic analysis; Public relations; Harm; Business; Political science; Medicine; Qualitative research; Sociology; Nursing; Public health; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004509743,0.0002073906,0.0004449726,0.0001130903,0.01074598,0.0002630486,0.0003913571,0.00012525,0.0003028967],"category_scores_gemma":[0.0005389881,0.0001914797,0.00007193268,0.00007408835,0.0001454336,0.00238997,0.0001962605,0.001345793,0.000001707537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005611003,"about_ca_system_score_gemma":0.0008751215,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1624059,"about_ca_topic_score_gemma":0.08316088,"domain_scores_codex":[0.9955983,0.002252342,0.001285689,0.0001510936,0.0002095199,0.0005031261],"domain_scores_gemma":[0.9940845,0.002684557,0.002241586,0.0004529663,0.000303191,0.0002332207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005862925,0.00009529619,0.07788485,0.0001781336,0.0001679116,0.000002228883,0.8866401,0.0003284656,0.0003109153,0.01512782,0.000147682,0.01853029],"study_design_scores_gemma":[0.008640142,0.002117442,0.1232186,0.001578332,0.0002759382,0.0000117419,0.6762038,0.0007019687,0.0003511067,0.1429767,0.04350724,0.0004169685],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650183,0.00002766302,0.02887738,0.002569364,0.0003414823,0.0006916058,0.00001251922,0.00002188116,0.002439775],"genre_scores_gemma":[0.9881052,0.0005138603,0.009999278,0.0008364427,0.000254726,0.00001920808,0.00004242142,0.00002301987,0.0002057854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2104363,"threshold_uncertainty_score":0.9905419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3119421363645553,"score_gpt":0.5854737971131144,"score_spread":0.2735316607485591,"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."}}