{"id":"W1996374865","doi":"10.1007/s11069-004-0785-x","title":"Computer-based Model for Flood Evacuation Emergency Planning","year":2005,"lang":"en","type":"article","venue":"Natural Hazards","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":210,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Flood myth; Emergency evacuation; Flooding (psychology); Flood stage; Population; Emergency management; Flood warning; Natural hazard; Warning system; Computer science; Environmental science; 100-year flood; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000913859,0.0001207782,0.0001001656,0.00006961427,0.00006396196,0.00001860768,0.00009769747,0.00008403898,0.00002953831],"category_scores_gemma":[0.00001257865,0.0001218838,0.00007636287,0.00009213301,0.000005394586,0.0001458283,0.0000076206,0.0001306506,0.00001991364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008615961,"about_ca_system_score_gemma":0.00002421354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.064538e-7,"about_ca_topic_score_gemma":0.00002133601,"domain_scores_codex":[0.9993461,0.000005978419,0.0001910553,0.0001194808,0.0001545817,0.0001827835],"domain_scores_gemma":[0.9997197,0.00001842546,0.00002312917,0.0001111228,0.00008263059,0.00004495228],"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":[0.000007775971,0.00001122114,0.00005092874,0.00002625566,0.00001171436,1.559137e-7,0.0001090147,0.9555471,0.0005962134,0.0003845664,0.004675881,0.03857917],"study_design_scores_gemma":[0.0004521877,0.00001508554,0.0004418615,0.00001169382,0.00001276169,6.431683e-7,0.000004541294,0.996905,0.0005113382,0.000170621,0.001314498,0.0001597996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1927693,0.0004408628,0.8048012,0.0002033783,0.0006658789,0.0001816015,0.00002351836,0.0003913643,0.0005229725],"genre_scores_gemma":[0.9585422,0.000006588766,0.04053378,0.0001323707,0.0003223268,0.0000241118,0.0001220509,0.00002634497,0.0002902625],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7657729,"threshold_uncertainty_score":0.4970276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166235400768828,"score_gpt":0.2792036205868687,"score_spread":0.2625800805099859,"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."}}