{"id":"W4382362514","doi":"10.52922/sb77048","title":"Identity crime and misuse in Australia 2023","year":2023,"lang":"en","type":"book","venue":"Australian Institute of Criminology eBooks","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identity theft; Hacker; Quarter (Canadian coin); Identity (music); Credit card; Cybercrime; Criminology; Personally identifiable information; Credit card fraud; Psychology; Computer security; Political science; Business; Law; The Internet; History; Finance; Payment","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005278946,0.0001295353,0.0001644488,0.002029096,0.001380203,0.001280402,0.0003185029,0.0003951404,0.006101002],"category_scores_gemma":[0.001999267,0.0002003219,0.0001754417,0.003044458,0.0008223185,0.001352474,0.001648205,0.0006456314,0.000991666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001512051,"about_ca_system_score_gemma":0.00270512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1133357,"about_ca_topic_score_gemma":0.189056,"domain_scores_codex":[0.999254,0.0001851607,0.00004941111,0.00003623664,0.0003926673,0.00008247206],"domain_scores_gemma":[0.9991417,0.0001395631,0.0002632523,0.0000338036,0.0002339263,0.0001877329],"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":[0.00004196367,0.0002372349,0.2838459,0.0009354401,0.00001787267,0.002253229,0.1353672,0.0002988504,0.0006595397,0.01587266,0.0790765,0.4813937],"study_design_scores_gemma":[0.000002723908,0.00009516756,0.8365281,0.000790665,0.000007766687,0.00278807,0.02697443,0.0003166899,0.0001356377,0.001543714,0.1307984,0.00001872504],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7975792,0.01918503,0.0003886951,0.009761963,0.0003101122,0.00009062914,0.0008090463,0.00004061865,0.1718347],"genre_scores_gemma":[0.9140743,0.02542809,0.0005087067,0.001587067,0.0001260703,0.00006254965,0.0004524009,0.00002672583,0.05773411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1133357,"threshold_uncertainty_score":0.2253521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1452133112431103,"score_gpt":0.3383583152532902,"score_spread":0.1931450040101799,"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."}}