{"id":"W2804572303","doi":"10.9734/jgeesi/2018/41773","title":"A Copula-based Approach for Assessing Flood Protection Overtopping Associated with a Seasonal Flood Forecast in Niamey, West Africa","year":2018,"lang":"en","type":"article","venue":"Journal of Geography Environment and Earth Science International","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"United Nations University Institute for Water, Environment, and Health; University of Ottawa","funders":"","keywords":"Flood myth; Tributary; Copula (linguistics); Flooding (psychology); Environmental science; Hydrology (agriculture); Flood forecasting; 100-year flood; Geography; Climatology; Geology; Mathematics; Geotechnical engineering; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001011541,0.0001561434,0.0001653566,0.0003607252,0.0002795083,0.0002156192,0.0003121014,0.00004352178,0.0001651443],"category_scores_gemma":[0.00004152527,0.0001231112,0.00008374274,0.0003906856,0.0007051308,0.0009967035,0.0001045969,0.0001528495,0.000002776984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001399276,"about_ca_system_score_gemma":0.00003938393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004448344,"about_ca_topic_score_gemma":0.00005797635,"domain_scores_codex":[0.9979779,0.00003359323,0.0003212792,0.0003242209,0.001012256,0.0003308226],"domain_scores_gemma":[0.9993606,0.00003128749,0.0003601812,0.00009485926,0.00003737271,0.0001157543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002730571,0.0009261039,0.9544773,0.00001232717,0.00009626185,0.000009974876,0.000347491,0.01710685,0.006498403,0.00007987264,0.00009754822,0.0200748],"study_design_scores_gemma":[0.001829959,0.000697029,0.8068578,0.0000892769,0.00003697748,0.00001393431,0.0001923396,0.1878781,0.0005022189,0.0001403569,0.001567578,0.000194505],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9117919,0.00002577027,0.08500448,0.0003118368,0.0001738203,0.0003949075,0.000005826891,0.00001141633,0.002280108],"genre_scores_gemma":[0.9720147,0.00001517932,0.02773312,0.0000613062,0.00009093469,0.00002715633,0.000005456639,0.000008727848,0.00004337596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1707712,"threshold_uncertainty_score":0.5020331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321607588490685,"score_gpt":0.2223697486630364,"score_spread":0.2091536727781295,"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."}}