{"id":"W2043494872","doi":"10.1080/19475705.2013.818066","title":"Estimating spatial disaster risk in urban environments","year":2013,"lang":"en","type":"article","venue":"Geomatics Natural Hazards and Risk","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Resilience (materials science); Vulnerability (computing); Hazard; Disaster risk reduction; Risk analysis (engineering); Risk management; Risk assessment; Emergency management; Environmental planning; Geospatial analysis; Environmental resource management; Spatial planning; Geographic information system; Vulnerability assessment; Population; Computer science; Business; Geography; Psychological resilience; Environmental science; Cartography; Computer security; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001134441,0.0006077066,0.0003200333,0.003830729,0.0004045164,0.0009788573,0.0004578815,0.000455048,0.000784049],"category_scores_gemma":[0.005001449,0.0003291006,0.0005056243,0.001799282,0.0004929606,0.0009678676,0.001554005,0.000196808,0.0001381385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008908759,"about_ca_system_score_gemma":0.000574592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01137241,"about_ca_topic_score_gemma":0.01163749,"domain_scores_codex":[0.9991708,0.0003816774,0.00006006099,0.00009422339,0.0002190569,0.00007426112],"domain_scores_gemma":[0.9979047,0.001339021,0.0003464665,0.0001387048,0.0002041522,0.00006703332],"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":[0.0001686982,0.00008401703,0.1727647,0.0001375169,0.0002617376,0.0005703358,0.0007649392,0.769051,0.002033073,0.006003187,0.0005394036,0.04762134],"study_design_scores_gemma":[0.00001345928,0.0001624399,0.09013481,0.00004716153,0.0001100992,0.0004981163,0.002434296,0.8921278,0.002569007,0.01013575,0.001694052,0.00007296564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8807135,0.000289114,0.1136076,0.0001093849,0.000008117577,0.0001466046,0.0007967086,0.0002717654,0.004057282],"genre_scores_gemma":[0.9798956,0.0001390996,0.01936632,0.00000356998,0.000004179935,0.00004031443,0.0002661161,0.000009432845,0.0002753305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01137241,"threshold_uncertainty_score":0.02261245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004733876096144772,"score_gpt":0.2380891502521995,"score_spread":0.2333552741560547,"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."}}