{"id":"W2049296874","doi":"10.1007/s00477-012-0632-7","title":"Risk assessment of agricultural irrigation water under interval functions","year":2012,"lang":"en","type":"article","venue":"Stochastic Environmental Research and Risk Assessment","topic":"Water resources management and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Irrigation; Agriculture; Interval (graph theory); Stochastic programming; Computer science; Farm water; Water supply; Water resource management; Irrigation district; Water resources; Risk analysis (engineering); Agricultural engineering; Water conservation; Mathematical optimization; Environmental science; Business; Mathematics; Environmental engineering; Engineering","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":[0.0006560446,0.0001671664,0.0001550342,0.0001508284,0.0002748913,0.00006299552,0.0001015096,0.00006205591,0.0002187655],"category_scores_gemma":[0.000006143602,0.0001127452,0.00004966962,0.00008855348,0.0001642024,0.0003590188,0.0001810705,0.0004011315,0.00003423055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002779309,"about_ca_system_score_gemma":0.000004545257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004443351,"about_ca_topic_score_gemma":0.0000104786,"domain_scores_codex":[0.9983694,0.0001336212,0.0002549704,0.0001869567,0.0005566421,0.0004984302],"domain_scores_gemma":[0.9995226,0.00007205974,0.00004643145,0.0001701949,0.00001694114,0.0001718319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003880778,0.0009724401,0.2556017,0.0001510189,0.0007669699,0.000001244256,0.001788589,0.7135617,0.01663371,0.001339643,0.0007417704,0.008402416],"study_design_scores_gemma":[0.0006103934,0.0003075135,0.937324,0.0000280559,0.000095877,0.000002414917,0.002390449,0.05732514,0.000897459,0.0005754269,0.0002234605,0.0002197853],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8323318,0.0001400098,0.1648243,0.00003455938,0.0001713641,0.0003928122,0.00004763034,0.00004198454,0.002015469],"genre_scores_gemma":[0.9971616,0.0003571275,0.001622587,0.000002501948,0.0001110984,0.00007569178,0.0002113869,0.0000232425,0.0004348253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6817223,"threshold_uncertainty_score":0.4597615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622450397189319,"score_gpt":0.2746506740822901,"score_spread":0.2584261701103969,"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."}}