{"id":"W2028408871","doi":"10.5539/ijps.v4n2p120","title":"Incorporating Land Cover within Bayesian Journey-to-crime Estimation Models","year":2012,"lang":"en","type":"article","venue":"International Journal of Psychological Studies","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Attractiveness; Cover (algebra); Land cover; Bayesian probability; Proxy (statistics); Psychology; Space (punctuation); Perception; Bayesian inference; Statistics; Econometrics; Land use; Geography; Computer science; Artificial intelligence; Ecology; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003718144,0.0005224285,0.0007993162,0.001128128,0.0003988738,0.001304456,0.001705664,0.0009999226,0.00192316],"category_scores_gemma":[0.01319948,0.0006288661,0.0007627317,0.001014316,0.0006449115,0.002248824,0.001293883,0.001173161,0.000305644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001013747,"about_ca_system_score_gemma":0.0007787565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01815731,"about_ca_topic_score_gemma":0.02351871,"domain_scores_codex":[0.9990281,0.0005606746,0.00004212156,0.0001471475,0.000105205,0.0001168272],"domain_scores_gemma":[0.9942974,0.004446079,0.0004872085,0.0002777275,0.000358455,0.0001331401],"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":[0.0001222562,0.00004781462,0.01158947,0.00001521166,0.00004866431,0.00005177009,0.0001044278,0.9632477,0.0001179211,0.009361935,0.0002150012,0.01507792],"study_design_scores_gemma":[0.000006619443,0.00001340985,0.001091688,0.000004570424,0.000006992325,0.00001422892,0.00001575288,0.9943869,0.00003676474,0.004292618,0.0001236451,0.000006766763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4524503,0.0002444625,0.5441007,0.0005450097,0.0000298622,0.0001257734,0.0003788733,0.0002206444,0.001904386],"genre_scores_gemma":[0.9271334,0.0002038448,0.07005495,0.00004974172,0.00003188027,0.0001210098,0.0003467779,0.00002847649,0.002029905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01815731,"threshold_uncertainty_score":0.03610325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2589757580017445,"score_gpt":0.5073532525923293,"score_spread":0.2483774945905848,"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."}}