{"id":"W2793653988","doi":"10.1080/08897077.2018.1449050","title":"One Size Fits All? Disentangling the Effects of Tobacco Taxes, Laws, and Control Spending on Adult Subgroups in the United States","year":2018,"lang":"en","type":"article","venue":"Substance Abuse","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"AcademyHealth; RAND Corporation","keywords":"Tobacco control; Behavioral Risk Factor Surveillance System; Population; Young adult; Demography; Current Population Survey; Quarter (Canadian coin); Medicine; Percentage point; Demographic economics; Environmental health; Gerontology; Public health; Economics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.008282578,0.0006004834,0.0009919116,0.001425272,0.0006230397,0.001354751,0.0008778897,0.0009344657,0.002275443],"category_scores_gemma":[0.017226,0.0003936127,0.002975611,0.001475699,0.001009037,0.001571447,0.001832106,0.001325364,0.0002514034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005774345,"about_ca_system_score_gemma":0.001055944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01875541,"about_ca_topic_score_gemma":0.02532062,"domain_scores_codex":[0.9949008,0.00318529,0.0002899624,0.0006892149,0.0004497309,0.0004848802],"domain_scores_gemma":[0.9856787,0.007033416,0.003720162,0.001683951,0.0007104744,0.001173428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001538171,0.00005568129,0.9904904,0.0000323769,0.00162837,0.00004137011,0.0001972668,0.0001770839,0.00005856535,0.0003390167,0.0004721508,0.006353706],"study_design_scores_gemma":[0.00002005937,0.0001664571,0.9940044,0.00009365613,0.001391824,0.00007661982,0.000845773,0.001069846,0.00008398733,0.001131673,0.001102974,0.00001275353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98686,0.004959648,0.001110495,0.003295722,0.0001165803,0.00005717457,0.001088985,0.00002072101,0.002490757],"genre_scores_gemma":[0.9982305,0.0004429498,0.0002189207,0.0005387882,0.00005289451,0.00001987191,0.0003668163,0.000009112662,0.0001202145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01875541,"threshold_uncertainty_score":0.04380298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01740862462888527,"score_gpt":0.2722049217006092,"score_spread":0.2547962970717239,"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."}}