{"id":"W2036072182","doi":"10.4296/cwrj251","title":"Aggregation of Inputs from Stakeholders for Flood Management Decision-Making in the Red River Basin","year":2004,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flood myth; Fuzzy logic; Flooding (psychology); Structural basin; Fuzzy set; Computer science; Process (computing); Set (abstract data type); Operations research; Environmental resource management; Management science; Environmental science; Geography; Mathematics; Engineering; Artificial intelligence; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009863825,0.0002888393,0.0003244547,0.0004854827,0.0005310682,0.0002138189,0.0009707625,0.0001061072,0.0001780352],"category_scores_gemma":[0.00006306475,0.0002074344,0.0001665262,0.0003657136,0.0003403692,0.0003816654,0.00009236657,0.0002679553,0.00001119241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383394,"about_ca_system_score_gemma":0.000005206097,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1783238,"about_ca_topic_score_gemma":0.8186849,"domain_scores_codex":[0.9975821,0.0001583749,0.0006196785,0.0004372784,0.0002902005,0.0009123934],"domain_scores_gemma":[0.9988128,0.000106938,0.0002250444,0.0004296487,0.00003865613,0.0003869215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002437531,0.0001580022,0.04320595,0.0001509608,0.0002877959,0.001502058,0.7798716,0.0821028,0.0004747267,0.00004522096,0.0004456174,0.09151155],"study_design_scores_gemma":[0.00258711,0.0004664508,0.07092606,0.00177661,0.0002317728,0.000153162,0.005722182,0.0009459511,0.002188016,0.05515002,0.8589762,0.0008764903],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944458,0.0001732554,0.001241871,0.001469963,0.0001594512,0.0006811881,0.00004394839,0.00001497374,0.001769575],"genre_scores_gemma":[0.9923475,0.0002091885,0.006428536,0.0006587107,0.0001283384,0.00004972408,0.00002553944,0.00003924079,0.0001132095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8585306,"threshold_uncertainty_score":0.8458927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01761437298142377,"score_gpt":0.2166280633706824,"score_spread":0.1990136903892587,"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."}}