{"id":"W1271145278","doi":"","title":"MAPPING OF INTERDEPENDENCIES THROUGH INTEGRATED HAZARD ANALYSIS: STUDY CASE OF A CANADIAN UNIVERSITY CAMPUS","year":2008,"lang":"en","type":"article","venue":"","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interdependence; Hazard; Scale (ratio); Computer science; Knowledge management; Operations research; Engineering; Sociology; Geography; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004405326,0.0004241121,0.0002968396,0.00182878,0.004092986,0.001403207,0.00155858,0.001024702,0.003032978],"category_scores_gemma":[0.001371773,0.0002816614,0.0004138884,0.003546212,0.001546495,0.0006004448,0.001380633,0.0006220147,0.0002106839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01634878,"about_ca_system_score_gemma":0.01721479,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9516255,"about_ca_topic_score_gemma":0.9708586,"domain_scores_codex":[0.9994757,0.00008283358,0.00001294154,0.00005534798,0.0001457025,0.0002275287],"domain_scores_gemma":[0.9993684,0.0001967633,0.00005334235,0.00004014682,0.000136313,0.0002050901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0009655395,0.001537873,0.2926339,0.0006888066,0.0001760518,0.02659083,0.03682997,0.3594031,0.01508557,0.0372563,0.009718589,0.2191135],"study_design_scores_gemma":[0.0002662605,0.0007332015,0.4217879,0.0002624134,0.0002183473,0.002161012,0.1491877,0.3566582,0.009439901,0.007571622,0.0513908,0.0003226566],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839632,0.000117001,0.00338307,0.0004067151,0.000006161803,0.0002006607,0.0004388947,0.0000605954,0.01142369],"genre_scores_gemma":[0.9938118,0.0001552511,0.003203343,0.00002488605,0.000002037841,0.00003766145,0.0001599955,0.000007612013,0.002597425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04837453,"threshold_uncertainty_score":0.1186193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409202232744746,"score_gpt":0.2106362746846564,"score_spread":0.1965442523572089,"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."}}