{"id":"W2527476712","doi":"10.2495/safe-v6-n3-455-465","title":"Estimation of flood risk management in 17th Century on Okayama Alluvial plain, Japan, by numerical flow simulation","year":2016,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"River Foundation","keywords":"Floodplain; Flood myth; Alluvium; Estimation; Flow (mathematics); Flood risk management; Alluvial plain; Environmental science; Geology; Hydrology (agriculture); Geography; Engineering; Geotechnical engineering; Geomorphology; Archaeology; Mathematics; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000342559,0.0003446963,0.0002508259,0.001330269,0.0004545111,0.0007752044,0.0003007459,0.0004916773,0.0006106165],"category_scores_gemma":[0.001117019,0.0002165364,0.00055122,0.0006113615,0.0002505644,0.0007802281,0.0003436669,0.0002173027,0.00006112672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001058918,"about_ca_system_score_gemma":0.0008278594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05041422,"about_ca_topic_score_gemma":0.03083442,"domain_scores_codex":[0.9998786,0.0000291899,0.00001440926,0.00002880328,0.00002195968,0.0000269665],"domain_scores_gemma":[0.9997776,0.000064138,0.00004413091,0.00001295973,0.00006821714,0.00003305977],"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":[0.0001060357,0.0001107078,0.2988852,0.00007417098,0.0001033435,0.0006857821,0.0007847263,0.673013,0.003191812,0.002763278,0.0004382278,0.01984374],"study_design_scores_gemma":[0.00001629958,0.00002941191,0.06451667,0.00001291129,0.00004738783,0.00005564015,0.0004916824,0.9331349,0.0005667696,0.0005229264,0.0005845702,0.00002079172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944284,0.00005250203,0.004451177,0.00004258772,0.000004378009,0.000009758654,0.00008443821,0.0000285776,0.0008981468],"genre_scores_gemma":[0.996533,0.00008381346,0.002806429,0.000004883993,0.000003926263,0.00001715005,0.0001531426,0.000005574133,0.0003920253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05041422,"threshold_uncertainty_score":0.1002415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002574167209197674,"score_gpt":0.2121998756624244,"score_spread":0.2096257084532267,"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."}}