{"id":"W2773846075","doi":"10.2495/safe-v8-n2-234-245","title":"Security assessment case studies of public buildings in India","year":2018,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public security; Poison control; Human factors and ergonomics; Injury prevention; Environmental planning; Forensic engineering; Environmental health; Engineering; Computer science; Geography; Political science; Medicine; Public administration","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":[0.001598332,0.0004315817,0.0003178277,0.003240427,0.004842475,0.002104946,0.002012485,0.001305586,0.006344691],"category_scores_gemma":[0.004173087,0.0003339078,0.0005230794,0.005014677,0.002650604,0.001456442,0.002512333,0.001155986,0.0006475186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007688881,"about_ca_system_score_gemma":0.002358414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07009102,"about_ca_topic_score_gemma":0.1752214,"domain_scores_codex":[0.997126,0.001473826,0.0001429096,0.0001545761,0.0005639265,0.0005387703],"domain_scores_gemma":[0.9952325,0.002292172,0.0004650416,0.0005463775,0.001000274,0.0004635993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001503635,0.003787178,0.3317353,0.002191126,0.0004231282,0.08467195,0.2607399,0.05704938,0.008968066,0.0502925,0.02019733,0.1784406],"study_design_scores_gemma":[0.00009512923,0.001113086,0.3134055,0.0005338957,0.0002013778,0.005960549,0.5565503,0.02386178,0.00606625,0.006470521,0.08555759,0.0001840988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746198,0.0002232263,0.001651405,0.000494039,0.0000202871,0.0002629945,0.0003775675,0.00005165051,0.02229898],"genre_scores_gemma":[0.9953231,0.0001520233,0.001247284,0.00002952456,0.000004857471,0.00003625009,0.0001358204,0.00001275539,0.003058421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07009102,"threshold_uncertainty_score":0.1393661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831180707155953,"score_gpt":0.3360936910598799,"score_spread":0.3177818839883203,"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."}}