{"id":"W4311357294","doi":"10.5539/cis.v16n1p49","title":"The Role of Digital Technologies in Combating Cyber-Trafficking in Persons Crimes","year":2022,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cyberspace; Human trafficking; The Internet; Emerging technologies; Business; Politics; Political science; Public relations; Computer security; Internet privacy; Criminology; Computer science; Sociology; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002550792,0.0003569286,0.0001741832,0.003438733,0.002884141,0.007249632,0.0007064861,0.001657693,0.008238541],"category_scores_gemma":[0.007113628,0.0001351713,0.0002971157,0.001538256,0.004558571,0.00817431,0.002483093,0.001737179,0.001353883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001957921,"about_ca_system_score_gemma":0.003651411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00340636,"about_ca_topic_score_gemma":0.004612778,"domain_scores_codex":[0.9976746,0.001411562,0.00008502238,0.0001211077,0.0004520272,0.0002556527],"domain_scores_gemma":[0.9940153,0.0030485,0.0009332837,0.0003018427,0.001087035,0.0006140505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005621093,0.0004567932,0.01485434,0.001246893,0.00004253444,0.001082708,0.01396928,0.001064492,0.001033906,0.4483705,0.03361493,0.4842074],"study_design_scores_gemma":[0.00002115528,0.0003073682,0.01992607,0.006037035,0.00006651996,0.002347872,0.05171616,0.002357494,0.00266137,0.1051178,0.8093809,0.00006032189],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09771459,0.05207235,0.01015483,0.0692222,0.001196629,0.0002294254,0.000098265,0.0001099016,0.7692019],"genre_scores_gemma":[0.8710572,0.07154001,0.01151266,0.007278516,0.0005652662,0.0001587822,0.00006918937,0.00003633347,0.03778205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008238541,"threshold_uncertainty_score":0.02756071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011280004280783,"score_gpt":0.2321501934193876,"score_spread":0.2220373933765798,"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."}}