{"id":"W3134819737","doi":"10.1177/0894439321994623","title":"Countering Distrust in Illicit Online Networks: The Dispute Resolution Strategies of Cybercriminals","year":2021,"lang":"en","type":"article","venue":"Social Science Computer Review","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Distrust; Computer security; Internet privacy; Resolution (logic); Political science; Computer science; Business; Criminology; Sociology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001084461,0.0001452592,0.0003561442,0.00004205153,0.000419848,0.0001983756,0.001184898,0.00002657451,0.000009599352],"category_scores_gemma":[0.00003778447,0.0001043102,0.0001181226,0.001745405,0.0004402485,0.0006991652,0.0009807793,0.0001487258,0.000002854958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009057411,"about_ca_system_score_gemma":0.0002065959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001677737,"about_ca_topic_score_gemma":0.0002350716,"domain_scores_codex":[0.9981173,0.000126576,0.0004855191,0.0003921058,0.0004927053,0.000385799],"domain_scores_gemma":[0.9991201,0.00007666367,0.0001421912,0.0003984073,0.0002203735,0.00004222415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000002619005,0.0001792016,0.0003776563,0.0007796033,0.00002949893,0.00002108325,0.002792096,0.0009619176,0.0001761238,0.6600623,0.002808774,0.3318091],"study_design_scores_gemma":[0.001712695,0.0004835129,0.4004307,0.0211246,0.0002788562,0.0001527928,0.004044121,0.2763841,0.0004239004,0.01155269,0.2808817,0.002530257],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02093796,0.08461474,0.8659073,0.01110186,0.002250245,0.001026711,0.00001451685,0.0001573591,0.01398938],"genre_scores_gemma":[0.9542124,0.03643111,0.005618325,0.003056031,0.0005709257,0.00003015611,0.00001215341,0.00001015441,0.00005871608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9332744,"threshold_uncertainty_score":0.4253645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03103573291317772,"score_gpt":0.3207752324560891,"score_spread":0.2897394995429114,"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."}}