{"id":"W4364860132","doi":"10.1109/icetems56252.2022.10093303","title":"Crime Prediction using Machine Learning","year":2022,"lang":"en","type":"article","venue":"","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003207697,0.00002381918,0.00003100554,0.0000377439,0.001289014,0.00002922616,0.00006549551,0.000008565298,0.0434104],"category_scores_gemma":[0.00002271382,0.00002542409,0.00004695843,0.0001044232,0.00002182918,0.00007612762,0.00005870741,0.0001055311,0.00001718876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008722424,"about_ca_system_score_gemma":0.00002060357,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01721461,"about_ca_topic_score_gemma":0.0004076109,"domain_scores_codex":[0.9994638,0.0001363945,0.0000710377,0.00007164363,0.0001605296,0.00009661011],"domain_scores_gemma":[0.9998882,0.00001138161,0.00002265003,0.0000364802,0.00001470961,0.000026524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003302187,0.0007134256,0.7192711,0.00002100774,0.0001023797,0.00001564403,0.03929931,0.007044347,0.0135434,0.1699939,0.03190089,0.01806166],"study_design_scores_gemma":[0.000168102,0.0001117136,0.008882538,0.000004715931,0.00001887454,0.000003557589,0.01664763,0.02627274,0.0001560319,0.0004563901,0.9471744,0.0001032599],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.590919,0.0001566486,0.005975551,0.0005762306,0.0008791485,0.0001331037,0.00002331443,0.0002333014,0.4011038],"genre_scores_gemma":[0.97508,0.000003951598,0.0001332818,0.00006466958,0.00008780149,0.000005290262,0.000007345747,0.000003570236,0.02461413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9152735,"threshold_uncertainty_score":0.991418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09214476671103308,"score_gpt":0.3775238266966279,"score_spread":0.2853790599855949,"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."}}