{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001622835,0.0001314628,0.0002512135,0.000355757,0.0008744526,0.0001229596,0.0003599299,0.0001358882,0.00004005923],"category_scores_gemma":[0.00002033244,0.0001038149,0.0001387624,0.0009256637,0.0006316557,0.0005452769,0.0001734233,0.0001291266,0.000003143034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003528145,"about_ca_system_score_gemma":0.00008003733,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005980899,"about_ca_topic_score_gemma":0.0262243,"domain_scores_codex":[0.9985184,0.000248144,0.0001524409,0.0003967511,0.000365233,0.0003190234],"domain_scores_gemma":[0.9993855,0.00003751737,0.00008479224,0.0002547764,0.0001763854,0.00006101551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"qualitative","study_design_scores_codex":[0.001216351,0.0006815773,0.1021623,0.001840583,0.01107602,0.00004111585,0.2560643,0.00127236,0.3452282,0.1049159,0.001148221,0.1743531],"study_design_scores_gemma":[0.003169042,0.001540118,0.0485859,0.0003050168,0.009525438,0.000003388278,0.7197396,0.01700508,0.03906251,0.003620888,0.156207,0.001236004],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482997,0.0001575547,0.03490144,0.01509595,0.00007749258,0.001020588,0.00006696043,0.0001400434,0.0002402615],"genre_scores_gemma":[0.9943215,0.00004734658,0.004742924,0.00001634516,0.00001138706,0.000004358585,0.00006503694,0.00000759176,0.0007834974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4636753,"threshold_uncertainty_score":0.9915445,"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."}}