{"id":"W7011210588","doi":"","title":"Local flood proofing programs","year":2005,"lang":"en","type":"other","venue":"US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flood myth; Outreach; Flood insurance; Public work; Local community; Flood control; State (computer science); Flood mitigation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002558973,0.00117538,0.0008472658,0.001814282,0.001837602,0.003776694,0.003295605,0.001390181,0.3313106],"category_scores_gemma":[0.008285938,0.0007043583,0.0009711494,0.001648652,0.001076063,0.005786717,0.005507474,0.002385293,0.1557747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00173425,"about_ca_system_score_gemma":0.002908806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00281423,"about_ca_topic_score_gemma":0.004442009,"domain_scores_codex":[0.997848,0.0004509027,0.0001030106,0.0003047654,0.0009086691,0.0003845849],"domain_scores_gemma":[0.9952267,0.001236373,0.0002777793,0.001343296,0.001433672,0.0004821771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004243002,0.0002211553,0.0008742442,0.0005154338,0.00002124376,0.0002093273,0.0004983266,0.002777604,0.002869881,0.07796375,0.6756226,0.238002],"study_design_scores_gemma":[0.00007764177,0.00007915228,0.000594712,0.0001585668,0.00001835227,0.0001613024,0.0002104978,0.006666448,0.004903642,0.02719713,0.9598917,0.00004081512],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007112581,0.0008747334,0.2498782,0.003321715,0.0009613914,0.000984222,0.01071249,0.09630092,0.6298538],"genre_scores_gemma":[0.08566596,0.002130457,0.1122974,0.001918328,0.0006431181,0.001455342,0.02168949,0.01719246,0.7570074],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3313106,"threshold_uncertainty_score":0.9538043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06539743797782016,"score_gpt":0.3180769154886106,"score_spread":0.2526794775107904,"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."}}