{"id":"W2891747940","doi":"10.1177/0091450918797355","title":"Six Years Later","year":2018,"lang":"en","type":"article","venue":"Contemporary Drug Problems","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Cannabis; Business; Advertising; Enforcement; Herbal supplement; Scope (computer science); Drug prices; Law enforcement; Commerce; Medicine; Economics; Monetary economics; Psychiatry; Alternative medicine; Law; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001014988,0.0005236359,0.0004554926,0.001263079,0.005110926,0.002908975,0.0008221767,0.001924419,0.2311769],"category_scores_gemma":[0.002805769,0.0002622443,0.000520301,0.00099557,0.0008582294,0.002316403,0.002734344,0.003361391,0.1198964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001946112,"about_ca_system_score_gemma":0.00301601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.013797,"about_ca_topic_score_gemma":0.03086599,"domain_scores_codex":[0.9990419,0.0001555213,0.00004946002,0.0001959113,0.0002159011,0.0003413965],"domain_scores_gemma":[0.998353,0.0000918072,0.00009318149,0.0001643038,0.000468552,0.0008291611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003893274,0.0006493776,0.02919631,0.0002559503,0.00004232842,0.002899241,0.006198091,0.0001463331,0.001149734,0.04884729,0.6471264,0.2630996],"study_design_scores_gemma":[0.00001351638,0.000113786,0.009721315,0.0001041969,0.000006295013,0.0008882308,0.002362168,0.00006616261,0.0002607321,0.001721022,0.9847247,0.00001786074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.09074669,0.006755091,0.003380478,0.05533137,0.0153749,0.0006332331,0.0104078,0.0009710948,0.8163994],"genre_scores_gemma":[0.07301543,0.001546624,0.00098745,0.01143419,0.000820434,0.0001172555,0.002361145,0.0001584984,0.9095589],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2311769,"threshold_uncertainty_score":0.7733639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02929019299200632,"score_gpt":0.2477677945093299,"score_spread":0.2184776015173236,"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."}}