{"id":"W2811383656","doi":"10.3390/w10070829","title":"Climate Change Impacts and Flood Control Measures for Highly Developed Urban Watersheds","year":2018,"lang":"en","type":"article","venue":"Water","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Universidade de São Paulo","keywords":"Environmental science; Climate change; Flooding (psychology); Impervious surface; Climatology; Flood myth; Return period; Flood control; Representative Concentration Pathways; Storm; Watershed; Water resource management; Climate model; Meteorology; Geography; Computer science","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":[0.000787687,0.0003295973,0.0002835977,0.0007995653,0.0002664225,0.0006006629,0.0003525284,0.0002774823,0.0006621782],"category_scores_gemma":[0.002093077,0.0001106939,0.0005676324,0.001144317,0.0004076178,0.0004593092,0.0004017082,0.0001998598,0.00003437919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001625606,"about_ca_system_score_gemma":0.001227286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03412244,"about_ca_topic_score_gemma":0.0464436,"domain_scores_codex":[0.9995803,0.0002063058,0.00001709806,0.00004355147,0.00007309828,0.00007969628],"domain_scores_gemma":[0.9993439,0.0002740209,0.000169134,0.00004376256,0.0001193364,0.00004970614],"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":[0.0003781274,0.0006077907,0.3551738,0.0002152637,0.0002910139,0.0007278424,0.0003514325,0.5830553,0.009352142,0.00752872,0.000907109,0.04141152],"study_design_scores_gemma":[0.00008894434,0.0006412977,0.5171969,0.00004222582,0.0002870474,0.00007204292,0.001392866,0.4692496,0.003401388,0.005269338,0.002318803,0.00003964003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956185,0.000161782,0.0018832,0.0001550508,0.000003426473,0.00003502002,0.0002368689,0.00002428916,0.001881858],"genre_scores_gemma":[0.9987223,0.0001017372,0.0009301446,0.000007933003,0.000002379903,0.00001151182,0.0001203399,0.000003315418,0.0001004041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03412244,"threshold_uncertainty_score":0.06784767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986604557068802,"score_gpt":0.2416035534338096,"score_spread":0.2217375078631216,"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."}}