{"id":"W4387752836","doi":"10.53328/inr23afv01","title":"Inequity Behind Levees, The Case of the United States of America","year":2023,"lang":"en","type":"report","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"United Nations University Institute for Water, Environment, and Health","funders":"Government of Canada; McMaster University","keywords":"Disadvantaged; Geography; Socioeconomic status; Levee; Poverty; Equity (law); Population; Socioeconomics; Flooding (psychology); Economic growth; Political science; Demography; Cartography; Sociology; Economics; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006366321,0.000137089,0.0001319254,0.001040158,0.002810779,0.001698739,0.0003319678,0.00064283,0.002812503],"category_scores_gemma":[0.002354413,0.00006026771,0.000215152,0.001571125,0.00092532,0.00164244,0.001456689,0.001235756,0.0001025389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504022,"about_ca_system_score_gemma":0.002117358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2192649,"about_ca_topic_score_gemma":0.3926365,"domain_scores_codex":[0.999476,0.0001519754,0.00002099952,0.00006691101,0.00010911,0.0001750517],"domain_scores_gemma":[0.9992418,0.000118339,0.0001605489,0.00005100148,0.0001778528,0.0002504453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005795059,0.0001188872,0.6998742,0.0001597416,0.00008561316,0.003166461,0.03719762,0.0002769835,0.0004263366,0.09273444,0.05523964,0.1106621],"study_design_scores_gemma":[0.000005768347,0.00005071024,0.7907127,0.0005505676,0.00005646808,0.002074829,0.08875243,0.0007822621,0.0001706615,0.01507141,0.1017365,0.00003571407],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8457225,0.007119109,0.0008024235,0.03833563,0.0004164659,0.00004760919,0.001170863,0.00001857501,0.1063668],"genre_scores_gemma":[0.9942741,0.001521686,0.0002463491,0.002212848,0.0001109109,0.00002230237,0.0002171385,0.000004889103,0.001389849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2192649,"threshold_uncertainty_score":0.4359772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06579076009259995,"score_gpt":0.3350592472937989,"score_spread":0.2692684872011989,"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."}}