{"id":"W2019436937","doi":"10.1080/14459790601157764","title":"The Security of Gambling and Gambling with Security: Hacking, Law Enforcement and Public Policy*","year":2007,"lang":"en","type":"article","venue":"International Gambling Studies","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Hacker; Law enforcement; Business; Crime control; Enforcement; State (computer science); Control (management); Internet privacy; Focus (optics); Computer security; Social control; Public security; Law and economics; Criminology; Public relations; Law; Political science; Psychology; Economics; Computer science; Criminal justice; Management","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":[0.001297621,0.0002324954,0.0002787828,0.000236847,0.0006956396,0.0003121899,0.0004738218,0.00004040186,0.000002134135],"category_scores_gemma":[0.0002835661,0.0001589212,0.00005395577,0.0003139901,0.0005165244,0.0005211114,0.0009597061,0.0001761756,0.000001144362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000088626,"about_ca_system_score_gemma":0.00004450436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001094773,"about_ca_topic_score_gemma":0.002091505,"domain_scores_codex":[0.9979688,0.00003125304,0.0004942682,0.0003888928,0.0006767229,0.0004400949],"domain_scores_gemma":[0.9982011,0.0006217713,0.0002363379,0.0002704813,0.0005886469,0.00008165431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003475102,0.00003593913,0.005444088,0.00004089722,0.0005602106,0.00000780877,0.007198084,0.00002384056,0.00006255371,0.9797586,0.0001110093,0.00672225],"study_design_scores_gemma":[0.009928112,0.001891905,0.01848326,0.002158757,0.0003530755,0.0004003349,0.05336955,0.03041972,0.019599,0.2428155,0.6173755,0.003205227],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8560674,0.02068366,0.03723591,0.01100528,0.001433676,0.0007597301,0.00001379687,0.0003179618,0.07248256],"genre_scores_gemma":[0.9951368,0.002874389,0.001114246,0.000497778,0.0002200002,0.00001516269,0.000001872267,0.00001092289,0.0001288189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.736943,"threshold_uncertainty_score":0.6480617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05398793813162722,"score_gpt":0.3542611183200365,"score_spread":0.3002731801884093,"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."}}