{"id":"W2508344553","doi":"10.3390/w8090377","title":"ResilSIM—A Decision Support Tool for Estimating Resilience of Urban Systems","year":2016,"lang":"en","type":"article","venue":"Water","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Western University","funders":"Federal Emergency Management Agency","keywords":"Damages; Flooding (psychology); Resilience (materials science); Natural disaster; Urbanization; Flood myth; Environmental planning; Hazard; Environmental resource management; Natural hazard; Emergency management; Urban planning; Population; Government (linguistics); Decision support system; Climate change; Risk analysis (engineering); Business; Computer science; Geography; Engineering; Environmental science; Civil engineering; Political science; Economics; Economic growth","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":[0.001683592,0.00133772,0.0008055008,0.003113515,0.0003789739,0.001641851,0.001489729,0.0007882238,0.01426125],"category_scores_gemma":[0.006268896,0.0004251524,0.0008615535,0.001058103,0.0002733052,0.001873631,0.001479866,0.0005438355,0.001962541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007632941,"about_ca_system_score_gemma":0.001078047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008142381,"about_ca_topic_score_gemma":0.0120742,"domain_scores_codex":[0.9991567,0.0002190497,0.00009569252,0.0001125318,0.0003573206,0.00005872495],"domain_scores_gemma":[0.9968138,0.002048908,0.0003355161,0.0001740257,0.0004762912,0.0001513567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001060553,0.0004910617,0.02600063,0.00178555,0.0005385082,0.0009480749,0.0009496495,0.3772846,0.009854615,0.01535964,0.07205377,0.4936733],"study_design_scores_gemma":[0.0001697123,0.0002315804,0.005048257,0.0001946893,0.0001019123,0.0002430959,0.0003733648,0.9419476,0.008500462,0.006612482,0.03643657,0.0001402978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.127729,0.0005322995,0.6680993,0.0007890193,0.0001369876,0.00137577,0.02875533,0.1475796,0.02500258],"genre_scores_gemma":[0.4868449,0.0002716441,0.4934658,0.0001577383,0.0000404327,0.0008469507,0.01186679,0.001313275,0.005192526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01426125,"threshold_uncertainty_score":0.04770863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008609951304718925,"score_gpt":0.2459176763541761,"score_spread":0.2373077250494572,"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."}}