{"id":"W2362631618","doi":"","title":"Integration of the GIS with Criminal Probability Model and Its Application","year":2013,"lang":"en","type":"article","venue":"Beijing Daxue xuebao. Ziran kexue ban","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Geospatial analysis; Crime analysis; Geographic information system; Scope (computer science); Data science; Computer science; Probabilistic logic; Population; Geography; Data mining; Criminology; Cartography; Artificial intelligence; Sociology","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":[0.0007694139,0.000670439,0.0006037942,0.00180162,0.0004073408,0.001329558,0.0008077984,0.0005335271,0.002941004],"category_scores_gemma":[0.002480834,0.0004421317,0.000841825,0.001708475,0.0004293261,0.001814154,0.0009380432,0.0004951653,0.000699053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006629934,"about_ca_system_score_gemma":0.0008449769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008543555,"about_ca_topic_score_gemma":0.003991514,"domain_scores_codex":[0.9993861,0.0002004515,0.00004974181,0.0001169406,0.0002213341,0.00002534873],"domain_scores_gemma":[0.999274,0.0003320472,0.00004924021,0.00009522541,0.000224558,0.00002500093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009546457,0.0001476355,0.01206375,0.0002466416,0.0002031862,0.0006087492,0.0003824051,0.5742378,0.004079106,0.1063629,0.007376565,0.2941957],"study_design_scores_gemma":[0.000005659499,0.00002493858,0.0007373161,0.00001378803,0.00002250048,0.000166793,0.00007148674,0.9754862,0.0009248171,0.01502263,0.007503216,0.00002048454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01443689,0.0002264406,0.9738887,0.0003510613,0.00008419971,0.00005928864,0.0001884876,0.001866961,0.008897958],"genre_scores_gemma":[0.4765322,0.0008121714,0.5156131,0.0001114794,0.00007880746,0.0001915343,0.0005598696,0.0002144855,0.005886282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008543555,"threshold_uncertainty_score":0.01698762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02211292679858632,"score_gpt":0.2012699185776992,"score_spread":0.1791569917791129,"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."}}