{"id":"W3175804400","doi":"10.1080/15564886.2021.1943090","title":"Conflict and Victimization in Online Drug Markets","year":2021,"lang":"en","type":"article","venue":"Victims & Offenders","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Negotiation; Ostracism; Context (archaeology); Database transaction; Business; Psychological intervention; Internet privacy; Criminology; Public relations; Computer security; Political science; Psychology; Social psychology; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0001362284,0.0001188658,0.000151072,0.00008775795,0.00009925663,0.00007532881,0.0001596598,0.00003372343,0.00005102429],"category_scores_gemma":[0.00003246843,0.0001190924,0.00003177862,0.0003689702,0.00003515755,0.0003152779,0.0002365323,0.00009796839,0.000008612299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003504488,"about_ca_system_score_gemma":0.00004488077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001426635,"about_ca_topic_score_gemma":0.0004818484,"domain_scores_codex":[0.9990467,0.00005631455,0.000187506,0.0003272249,0.0001682944,0.0002139814],"domain_scores_gemma":[0.999522,0.00007664871,0.00003618424,0.0002616344,0.0000497671,0.0000537171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002182583,0.002323767,0.2330823,0.0005540595,0.0009540963,0.001201336,0.09462935,0.005684824,0.005916529,0.1665052,0.1044767,0.3844536],"study_design_scores_gemma":[0.004711087,0.0001088107,0.5796335,0.0002081764,0.00004845415,0.00009277701,0.006006613,0.1354218,0.004539318,0.001677704,0.2663786,0.001173266],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7552121,0.006935005,0.1190206,0.01698538,0.001998075,0.0007726276,0.00001713205,0.0006716921,0.09838736],"genre_scores_gemma":[0.9891412,0.001272986,0.006088801,0.001950444,0.0000461391,0.000009833299,0.00002244174,0.00001122522,0.001456889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3832803,"threshold_uncertainty_score":0.4856445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692049397654802,"score_gpt":0.2454695359138107,"score_spread":0.2285490419372627,"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."}}