{"id":"W2320963963","doi":"10.1061/41173(414)306","title":"A Framework for Estimating Downstream Environmental Impacts of Reservoir Extreme Outflows","year":2011,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2011","topic":"Water resources management and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vulnerability (computing); Flood myth; Environmental science; Hazard; Downstream (manufacturing); Probabilistic logic; Resilience (materials science); Population; Environmental resource management; Term (time); Climate change; Dam break; Vulnerability assessment; Psychological resilience; Computer science; Geography; Ecology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001170502,0.0003024394,0.0002803572,0.0001683904,0.0001167865,0.00003826422,0.0002199743,0.00008624596,0.0009941553],"category_scores_gemma":[0.000002282786,0.0002369667,0.00009328577,0.00002888339,0.0002040609,0.0002199092,0.0001858179,0.0001139017,0.00005149883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003925003,"about_ca_system_score_gemma":5.248914e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003158339,"about_ca_topic_score_gemma":0.00001793496,"domain_scores_codex":[0.9986984,0.0000247136,0.0003692216,0.000297189,0.0001835381,0.0004269676],"domain_scores_gemma":[0.9994735,0.00002899164,0.00007566981,0.0002832202,0.000001883386,0.0001368047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00171714,0.001421461,0.7036418,0.002387268,0.001765109,0.00009711158,0.08913113,0.03544449,0.07352009,0.0004441281,0.003415674,0.08701465],"study_design_scores_gemma":[0.009094396,0.00147286,0.1126672,0.001053848,0.001050553,0.00005280735,0.004074471,0.3495193,0.3934775,0.01035541,0.1121138,0.005067823],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938063,0.000479727,0.003294384,0.00002164208,0.0002282068,0.0004761757,0.00007042334,0.0001061399,0.001516975],"genre_scores_gemma":[0.9693668,0.00008490797,0.02906934,0.00002600914,0.00009020697,0.0000573749,0.00009171224,0.00006619597,0.001147473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5909745,"threshold_uncertainty_score":0.9999191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02008961967756934,"score_gpt":0.1880985783140023,"score_spread":0.168008958636433,"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."}}