{"id":"W7028683106","doi":"","title":"Gambling-related harms: Developing priorities for harm reduction policy setting","year":2019,"lang":"en","type":"article","venue":"Digital Scholarship - UNLV (University of Nevada Reno)","topic":"Physics and Engineering Research Articles","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Greo","funders":"Gambling Research Exchange Ontario; University of Waterloo","keywords":"Harm reduction; Operationalization; Harm; Stakeholder; Public policy; Work (physics); Policy analysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001516023,0.0001340893,0.0001724694,0.0002028328,0.000109819,0.0001225056,0.000230269,0.00007494078,0.00001561056],"category_scores_gemma":[0.000067181,0.0001738538,0.000090128,0.0003696027,0.00004453256,0.001603435,0.00007279787,0.000206411,0.00004922287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002051889,"about_ca_system_score_gemma":0.0000829668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002790924,"about_ca_topic_score_gemma":0.000002030455,"domain_scores_codex":[0.9991239,0.000008775713,0.0001287392,0.0001786092,0.0002033356,0.0003566621],"domain_scores_gemma":[0.9995288,0.00006229971,0.00003809534,0.0001659825,0.00009973301,0.0001051105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002991715,0.0001668341,0.01072961,0.003008584,0.001160369,0.00002828315,0.01007678,0.08459157,0.4271475,0.04094668,0.001560264,0.4202843],"study_design_scores_gemma":[0.01825196,0.001571822,0.1925225,0.004499791,0.0002927091,0.0001568192,0.03067821,0.2875357,0.1154453,0.2545401,0.0872284,0.007276817],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954207,0.00009621603,0.001614016,0.0002492116,0.0001331212,0.0002188871,0.00007384962,0.0002401331,0.001953868],"genre_scores_gemma":[0.9982154,0.00004123138,0.00133308,0.000004912677,0.00004965415,6.025204e-7,0.00004715232,0.00002928046,0.000278635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4130075,"threshold_uncertainty_score":0.7089552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02061655684336669,"score_gpt":0.2325690229809988,"score_spread":0.2119524661376321,"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."}}