{"id":"W2800654834","doi":"10.1080/17440572.2018.1460951","title":"Illicit payments for illicit goods: noncontact drug distribution on Russian online drug marketplaces","year":2018,"lang":"en","type":"article","venue":"Global Crime","topic":"Crime, Illicit Activities, and Governance","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Payment; Illicit drug; Business; Internet privacy; The Internet; Enforcement; Distribution (mathematics); Drug; Law enforcement; Street drugs; Consumption (sociology); Commerce; Advertising; Computer security; Marketing; Computer science; Pharmacology; Finance; Medicine; Law; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006435432,0.0003192895,0.0003644788,0.00003140706,0.001012872,0.0001927124,0.0005399006,0.0001504072,0.000258761],"category_scores_gemma":[0.0003809649,0.0002990361,0.0002132478,0.000350634,0.0004327253,0.0004424352,0.0000734554,0.0001529628,0.0001640186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001015974,"about_ca_system_score_gemma":0.0002581076,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0271027,"about_ca_topic_score_gemma":0.02523456,"domain_scores_codex":[0.9972614,0.0001893238,0.0003663092,0.0005757742,0.00073809,0.0008691206],"domain_scores_gemma":[0.9986954,0.0002439906,0.0002777358,0.0003627834,0.0001443454,0.0002757749],"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":[0.002011171,0.00170463,0.01752144,0.0001054009,0.0002624462,0.00001754218,0.01328551,0.000005219557,0.0002372305,0.2973847,0.6229827,0.04448199],"study_design_scores_gemma":[0.001043769,0.0002433942,0.05050487,0.0001160388,0.00006651795,0.000001564252,0.004245961,0.00005382534,0.0007534949,0.004445234,0.9380057,0.0005196158],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8472384,0.0002796994,0.0004908477,0.004354676,0.002371046,0.001031719,0.006963384,0.0002839873,0.1369863],"genre_scores_gemma":[0.9868708,0.0001282015,0.0001916964,0.001159976,0.002142364,0.00003837919,0.0002740201,0.0000220142,0.009172607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.315023,"threshold_uncertainty_score":0.9999462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099908994490769,"score_gpt":0.3297317728509024,"score_spread":0.3087326829059947,"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."}}