{"id":"W2802634149","doi":"10.1007/s11269-018-1983-8","title":"Integrating Social Dimensions into Flood Cost Forecasting","year":2018,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; McMaster University","funders":"","keywords":"Hydrogeology; Flood myth; Water resource management; Computer science; Environmental science; Geography; Engineering; Geotechnical engineering; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001219232,0.0003737844,0.0003224676,0.001980288,0.00037367,0.001544051,0.0004621456,0.0006454478,0.003877579],"category_scores_gemma":[0.008836097,0.0002186649,0.0003255202,0.002540235,0.0003348466,0.002850665,0.0006717421,0.0007960025,0.000344806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001116096,"about_ca_system_score_gemma":0.0007627902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01797984,"about_ca_topic_score_gemma":0.03688208,"domain_scores_codex":[0.9995926,0.0001973373,0.00003164879,0.00004325365,0.0001000614,0.00003506588],"domain_scores_gemma":[0.9954736,0.00328431,0.0003557998,0.0001914548,0.0005215925,0.0001732822],"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":[0.0001635137,0.0003884633,0.1951357,0.0001140948,0.0003050556,0.0001664475,0.0003635538,0.5455137,0.0007572208,0.04176144,0.005716732,0.2096141],"study_design_scores_gemma":[0.000005597567,0.00003695054,0.01991177,0.00002201184,0.00003013009,0.00002051809,0.0003167247,0.9402237,0.0002505969,0.03704961,0.002112524,0.00001985095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6700282,0.001034451,0.2849475,0.00451351,0.0002821356,0.0001900279,0.002802601,0.0003587229,0.03584281],"genre_scores_gemma":[0.9727931,0.0002512619,0.02500154,0.00004276166,0.00005377224,0.00003913995,0.0004432861,0.00002176072,0.001353352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01797984,"threshold_uncertainty_score":0.03575033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581180621877038,"score_gpt":0.239912234079026,"score_spread":0.2241004278602557,"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."}}