{"id":"W223699652","doi":"","title":"Combatting the Contraband Tobacco Trade in Canada","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fraser Institute","funders":"","keywords":"Excise; Enforcement; Business; Black market; Law enforcement; Tobacco industry; Revenue; Tax revenue; International trade; Political science; Law; Finance","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.00181152,0.00027688,0.0002995692,0.001616625,0.01277374,0.005364797,0.001404996,0.002306772,0.003913173],"category_scores_gemma":[0.004049824,0.0002937384,0.0004092289,0.002453427,0.004071746,0.001156767,0.002357445,0.002936642,0.0001828937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1210608,"about_ca_system_score_gemma":0.394978,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9965804,"about_ca_topic_score_gemma":0.997781,"domain_scores_codex":[0.9956349,0.000245166,0.00008346931,0.0002001759,0.001454636,0.002381745],"domain_scores_gemma":[0.9951881,0.0003971393,0.0003917739,0.0001010588,0.001589899,0.002331996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000874153,0.0003846985,0.108854,0.000609484,0.0001115487,0.00236249,0.02265903,0.005875717,0.003032244,0.5687069,0.1285216,0.158795],"study_design_scores_gemma":[0.00008774834,0.0001886447,0.1814606,0.0008996697,0.0001497182,0.0004326547,0.0267824,0.00675208,0.001885878,0.02385513,0.7573036,0.000201984],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3654802,0.01687502,0.00321759,0.2875559,0.0008467303,0.0004477742,0.0006916633,0.0001786265,0.3247065],"genre_scores_gemma":[0.9209262,0.009497091,0.002603921,0.02193231,0.0001223635,0.0000588366,0.0002252798,0.00002395673,0.04460995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1210608,"threshold_uncertainty_score":0.8783618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01481081954489358,"score_gpt":0.2282611888978523,"score_spread":0.2134503693529587,"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."}}