{"id":"W7110496498","doi":"","title":"DESIGNING AN INTEGRATED SOLUTION FOR THE ALA WAI WATERSHED: ANALYSIS OF PROPOSALS, GLOBAL FLOOD MITIGATION PROJECTS, AND WATER QUALITY IMPROVEMENT TECHNOLOGY","year":2024,"lang":"en","type":"article","venue":"ScholarSpace (University of Hawaii at Manoa)","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Marine Fisheries Service; U.S. Army Corps of Engineers; Federal Emergency Management Agency; U.S. Army; U.S. Department of Agriculture; U.S. Fish and Wildlife Service; National Oceanic and Atmospheric Administration; Fondation Pour La Conservation Du Saumon Atlantique; American Association of Endodontists Foundation","keywords":"Water quality; Flood myth; Flood mitigation; Quality (philosophy); Quality management; Water pollution; Work (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.005580362,0.0003596416,0.0002208726,0.001376151,0.001965582,0.004914014,0.000846836,0.001649866,0.005048869],"category_scores_gemma":[0.005852102,0.0003264644,0.0006535648,0.001715414,0.001120067,0.003040512,0.001961274,0.0008370186,0.0004125328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003154745,"about_ca_system_score_gemma":0.01081389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0092705,"about_ca_topic_score_gemma":0.02856418,"domain_scores_codex":[0.9977846,0.000934394,0.00009871666,0.0001783676,0.0005731375,0.000430808],"domain_scores_gemma":[0.9977466,0.0009287132,0.0002786237,0.0001876324,0.0006242231,0.0002340838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007316151,0.002516618,0.08818195,0.0008472432,0.0003814028,0.00144345,0.009483143,0.2191377,0.03395303,0.1832571,0.009783701,0.4502829],"study_design_scores_gemma":[0.0006651283,0.004542485,0.07848673,0.0006342693,0.001225853,0.0005884309,0.07970489,0.5773979,0.03465021,0.09006131,0.1318304,0.0002123049],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8487757,0.0001881005,0.1040652,0.003744993,0.00003859062,0.001350524,0.0001774705,0.0002447274,0.04141468],"genre_scores_gemma":[0.8570991,0.0002207293,0.1357018,0.0001920511,0.000007604154,0.0003734328,0.0001967011,0.00006752631,0.006141094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0092705,"threshold_uncertainty_score":0.02951217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02061025356294165,"score_gpt":0.2774859264625605,"score_spread":0.2568756728996188,"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."}}