{"id":"W4234822349","doi":"10.4018/9781599045917.ch011","title":"Crime Simulation Using GIS and Artificial Intelligent Agents","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Esri (Canada)","funders":"","keywords":"Computer science; Reinforcement learning; Mobile agent; Crime analysis; Artificial intelligence; Computer security; Data science; Distributed computing; Criminology","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":[0.00008714857,0.0002359296,0.0002217962,0.00007916395,0.00009586251,0.0002333822,0.0003794603,0.0001804033,0.00004361406],"category_scores_gemma":[0.00001423529,0.0002436839,0.00007469794,0.00002249573,0.00006038859,0.0001199279,0.000353795,0.00009489146,0.000111435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009045004,"about_ca_system_score_gemma":0.0000829451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003997558,"about_ca_topic_score_gemma":0.000008426665,"domain_scores_codex":[0.9987835,0.00001514533,0.0003316467,0.0004176731,0.000273797,0.0001782598],"domain_scores_gemma":[0.9991397,0.00001434441,0.0001921747,0.0004188437,0.0001058017,0.0001291079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003027049,0.000007042678,0.000004197805,0.00001083745,0.00002629324,0.00001402399,0.00007514183,0.0001726635,0.000003552165,0.9837136,0.0001991757,0.01577051],"study_design_scores_gemma":[0.0001036682,0.00005705231,0.00002998315,0.0001444057,0.00008336511,0.00001482085,0.000004012386,0.3137094,0.00009935873,0.6441499,0.04108344,0.0005205352],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0000387693,0.00005431244,0.4498415,0.000005474338,0.0003482747,0.0001236437,0.00004481662,0.00008693643,0.5494563],"genre_scores_gemma":[0.9111766,0.00002720012,0.01400249,0.002370111,0.0007209866,0.000003101876,0.00004078447,0.00009558076,0.07156315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9111378,"threshold_uncertainty_score":0.993714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1209200232104979,"score_gpt":0.341446280273299,"score_spread":0.2205262570628012,"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."}}