{"id":"W2015432065","doi":"10.1108/pijpsm-03-2013-0025","title":"Base rates and Bayes’ Theorem for decision support","year":2014,"lang":"en","type":"article","venue":"Policing An International Journal","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; York University; Toronto Metropolitan University","funders":"","keywords":"Categorical variable; Bayes' theorem; Originality; Sample (material); Base (topology); Computer science; Statistics; Advice (programming); Variable (mathematics); Psychology; Mathematics; Econometrics; Artificial intelligence; Machine learning; Social psychology; Bayesian probability","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":[0.1295964,0.002665029,0.003897056,0.005769178,0.001417755,0.008014215,0.004591243,0.00410975,0.008116873],"category_scores_gemma":[0.3790816,0.001440446,0.002459381,0.003479046,0.006193712,0.01009893,0.002809363,0.007666528,0.002665594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003936303,"about_ca_system_score_gemma":0.004238436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004666788,"about_ca_topic_score_gemma":0.001542925,"domain_scores_codex":[0.8971828,0.08184448,0.003493898,0.005414906,0.01108576,0.0009782049],"domain_scores_gemma":[0.5324791,0.4387765,0.006528273,0.009727841,0.01143063,0.001057562],"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":[0.0006421473,0.0002200197,0.007823232,0.001211105,0.0006943354,0.0003047978,0.0011923,0.194106,0.0002478192,0.5746409,0.01084925,0.2080681],"study_design_scores_gemma":[0.0001327194,0.0001601198,0.0006768148,0.0005347145,0.00007392488,0.0001647507,0.0001506535,0.3850593,0.0004143787,0.6068695,0.005673177,0.00009004017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004837157,0.001702556,0.9830493,0.003617377,0.0003792861,0.000271953,0.0002051971,0.0004560414,0.005481225],"genre_scores_gemma":[0.2528444,0.002130771,0.7381559,0.001353175,0.001266094,0.0017118,0.000397431,0.0001968145,0.001943553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1295964,"threshold_uncertainty_score":0.6853796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04933729708182575,"score_gpt":0.4344552533875942,"score_spread":0.3851179563057684,"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."}}