{"id":"W2021030836","doi":"10.1504/ijem.2007.013994","title":"Vulnerability index construction: methodological choices and their influence on identifying vulnerable neighbourhoods","year":2007,"lang":"en","type":"article","venue":"International Journal of Emergency Management","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vulnerability (computing); Variable (mathematics); Weighting; Vulnerability assessment; Emergency management; Flooding (psychology); Index (typography); Environmental planning; Risk analysis (engineering); Computer science; Geography; Operations research; Environmental resource management; Business; Engineering; Political science; Computer security; Economics; Psychology; Psychological resilience; Mathematics; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002946059,0.0001747249,0.0001867597,0.0001823774,0.000148364,0.0000598767,0.0005362697,0.00004552542,0.002322371],"category_scores_gemma":[0.00009858922,0.0001301555,0.0001107782,0.0001882516,0.0001006578,0.0004993436,0.0003922116,0.0002830621,0.00002570303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001793085,"about_ca_system_score_gemma":0.000004110409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000899497,"about_ca_topic_score_gemma":0.00006370189,"domain_scores_codex":[0.9979658,0.0001503383,0.0006712918,0.0002717634,0.0007088535,0.0002319234],"domain_scores_gemma":[0.9991279,0.0001278805,0.0004055527,0.0001610825,0.00006729749,0.0001102871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005425738,0.0006942254,0.6105644,0.0000528143,0.0009978225,0.0002249079,0.000606845,0.02513301,0.002282317,0.02939609,0.003835199,0.3256698],"study_design_scores_gemma":[0.0009797808,0.0002533845,0.9235143,0.00006128902,0.00005537178,0.0000382595,0.001266362,0.0006394348,0.001125876,0.03128943,0.04047836,0.0002981672],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8231772,0.0001156927,0.1384315,0.0008377872,0.003498808,0.0002273453,0.00000199596,0.00002341892,0.03368623],"genre_scores_gemma":[0.9849557,0.0007993127,0.01325801,0.0002326518,0.000208444,0.000004951296,0.000001216595,0.000008273091,0.0005314201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3253716,"threshold_uncertainty_score":0.9985896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05020591127382503,"score_gpt":0.3676523550847953,"score_spread":0.3174464438109703,"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."}}