{"id":"W3037569612","doi":"10.3390/w12061793","title":"Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India","year":2020,"lang":"en","type":"article","venue":"Water","topic":"Water resources management and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Resource (disambiguation); Computer science; Vulnerability (computing); Probabilistic logic; Water resources; Risk analysis (engineering); Reliability (semiconductor); Population; Environmental science; Environmental resource management; Operations research; Systems engineering; Management science; Engineering; Business","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":[0.0001018423,0.0001283914,0.0001569732,0.00007183258,0.00004074703,0.00008209871,0.00008878954,0.00005214965,0.00001691],"category_scores_gemma":[0.000004066574,0.00008162495,0.00002409731,0.00006085791,0.00001088387,0.000128229,0.00005634783,0.00009026381,0.0001429051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004089565,"about_ca_system_score_gemma":5.937145e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001427144,"about_ca_topic_score_gemma":0.00001520601,"domain_scores_codex":[0.9992117,0.00003560972,0.0002483649,0.000193021,0.0000960429,0.0002152191],"domain_scores_gemma":[0.9997841,0.000007259967,0.000009319405,0.0001414287,0.00001669835,0.00004126482],"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":[0.0000121784,0.000004550282,0.0001903248,0.00007797047,0.00004107678,0.0001409833,0.01347419,0.984338,0.001200564,0.000009040548,0.0004402841,0.0000708541],"study_design_scores_gemma":[0.0002458984,0.000008335435,0.000005164778,0.00001863939,0.00001760166,0.000003336416,0.001606407,0.9885439,0.003309859,0.00002993453,0.006063001,0.0001478687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921569,0.0002332061,0.006198442,0.0003315519,0.0001450741,0.0002301465,0.000004693181,0.0002244447,0.0004755807],"genre_scores_gemma":[0.9993333,0.00001914182,0.00007416247,0.00006764594,0.0001279942,0.00002876358,0.0002109604,0.000028387,0.0001096247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01186778,"threshold_uncertainty_score":0.3328569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04557515089426966,"score_gpt":0.2253117719929892,"score_spread":0.1797366210987196,"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."}}