{"id":"W4415360528","doi":"10.59934/jaiea.v5i1.1658","title":"Prediction of Criminal Theft Locations at the Binjai Police Station using Historical Data and the KNN Algorithm","year":2025,"lang":"","type":"article","venue":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Government (linguistics); Traffic police; Pattern recognition (psychology); Statistical classification; Contextual design","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005432407,0.0007946698,0.0005307037,0.003155416,0.0004489708,0.000895721,0.0007171616,0.0005561037,0.0007578618],"category_scores_gemma":[0.002822265,0.0003390594,0.0004300486,0.001927269,0.000227104,0.001005854,0.0004259195,0.000607303,0.0005290489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007652114,"about_ca_system_score_gemma":0.0007466026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02980347,"about_ca_topic_score_gemma":0.02455376,"domain_scores_codex":[0.9996638,0.00005133172,0.00003824178,0.0001022298,0.00009288469,0.00005152133],"domain_scores_gemma":[0.9989415,0.0003352558,0.0002486065,0.00007995882,0.0003232328,0.00007147695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003064878,0.0004033251,0.3574252,0.0001928861,0.0001470596,0.0006201278,0.0002265066,0.4951444,0.002482696,0.0008964242,0.003262396,0.1388924],"study_design_scores_gemma":[0.000007881097,0.00007929124,0.04660079,0.00004109176,0.00002669013,0.0001148321,0.0002478909,0.9500316,0.001308212,0.0004907969,0.001026054,0.00002483766],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950534,0.0004920741,0.04253756,0.0002248726,0.0001129407,0.00009028512,0.002697412,0.0006135372,0.002697153],"genre_scores_gemma":[0.9755189,0.0003765636,0.02004998,0.00001229352,0.00002543871,0.00003720778,0.003044054,0.00002083661,0.0009147351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02980347,"threshold_uncertainty_score":0.05925995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0659592560163019,"score_gpt":0.3140605746167451,"score_spread":0.2481013186004432,"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."}}