{"id":"W4280510155","doi":"10.3390/w14101541","title":"Conjunctive Water Management under Multiple Uncertainties: A Case Study of the Amu Darya River Basin, Central Asia","year":2022,"lang":"en","type":"article","venue":"Water","topic":"Water resources management and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"National Natural Science Foundation of China","keywords":"Water scarcity; Water resource management; Groundwater; Conjunctive use; Water resources; Population; Environmental science; Drainage basin; Surface water; Structural basin; Streamflow; Stochastic programming; Computer science; Operations research; Agriculture; Environmental engineering; Mathematical optimization; Engineering; Mathematics; Geography; Aquifer; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001595643,0.0008558725,0.0008159854,0.0007873016,0.001251822,0.001531804,0.001034958,0.001369397,0.001059055],"category_scores_gemma":[0.002071872,0.0004660235,0.001121714,0.001341869,0.001045562,0.001202543,0.00120619,0.0007764902,0.00004427068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002209995,"about_ca_system_score_gemma":0.001824293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03472348,"about_ca_topic_score_gemma":0.03861478,"domain_scores_codex":[0.9992105,0.0004123608,0.00002567349,0.0001242603,0.00009173712,0.000135391],"domain_scores_gemma":[0.9988111,0.0008205748,0.000129187,0.0000498187,0.0001027463,0.0000865047],"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":[0.0001009441,0.0001722263,0.01285281,0.00007249375,0.0001216777,0.002190966,0.0001970892,0.9715171,0.001212101,0.003674889,0.000335388,0.007552311],"study_design_scores_gemma":[0.00003276896,0.0001310106,0.004290259,0.000009290668,0.00005919399,0.0001153977,0.0006781545,0.9906882,0.0006990702,0.002890034,0.0003819065,0.00002457887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721444,0.0001870777,0.02432181,0.0002811788,0.0000117371,0.00008376563,0.0001475892,0.00004993248,0.002772578],"genre_scores_gemma":[0.9943051,0.0000698307,0.005230001,0.00001540614,0.000004004397,0.0000318331,0.00003506974,0.000005240366,0.0003034028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03472348,"threshold_uncertainty_score":0.06904268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009323356770295771,"score_gpt":0.1796263307968674,"score_spread":0.1703029740265716,"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."}}