{"id":"W1989621295","doi":"10.1016/j.scitotenv.2010.02.014","title":"Modeling climate change impacts on water trading","year":2010,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Water resources management and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina; University of Manitoba","funders":"","keywords":"Climate change; Environmental science; Water balance; Watershed; Water resources; Emissions trading; Term (time); Water supply; Water trading; Environmental resource management; Computer science; Environmental engineering; Water conservation; Engineering; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000335286,0.00007210377,0.00004853294,0.00003501476,0.0001637884,0.00003121969,0.0003434166,0.00001419836,0.00004803361],"category_scores_gemma":[0.000002524701,0.0000330369,0.00003160232,0.00005833489,0.0001403933,0.0001391882,0.0001426159,0.00009668071,0.00003322625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002717128,"about_ca_system_score_gemma":7.112984e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005603818,"about_ca_topic_score_gemma":2.558979e-7,"domain_scores_codex":[0.9993411,0.000006285444,0.0000854973,0.0000897362,0.0002471931,0.0002301665],"domain_scores_gemma":[0.9996728,0.000003269504,0.00001266363,0.000281105,0.000001563475,0.00002864126],"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":[0.000001817273,0.000005911289,0.000002542531,0.000004803136,0.000002057102,7.336735e-8,0.0008264013,0.8985677,0.100062,0.00009040066,0.000002172972,0.0004341],"study_design_scores_gemma":[0.00005199734,0.00001190127,0.0003586373,0.000009270757,0.000007125261,8.120536e-7,0.00003065374,0.8999701,0.09939759,0.00009475597,0.00001468359,0.00005251533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968259,0.000006526703,0.0001310994,0.0003013632,0.0002490529,0.0001625669,9.347371e-7,0.00002402689,0.002298513],"genre_scores_gemma":[0.9997649,0.00001817215,0.00009068091,0.00001099994,0.00004686174,0.000006790975,3.811913e-7,0.000008806545,0.00005237279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002939018,"threshold_uncertainty_score":0.1347206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01423429357801306,"score_gpt":0.1822696328812181,"score_spread":0.168035339303205,"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."}}