{"id":"W2123981771","doi":"10.1007/s11270-014-1895-z","title":"Inexact Left-Hand-Side Chance-Constrained Programming for Nonpoint-Source Water Quality Management","year":2014,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Water resources management and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonpoint source pollution; Constraint (computer-aided design); Linearization; Mathematical optimization; Water quality; Interval (graph theory); Linear programming; Quality (philosophy); Computer science; Mathematics; Nonlinear system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002837444,0.001446391,0.002588502,0.0007912525,0.0006252624,0.002198953,0.002102234,0.002973515,0.005202217],"category_scores_gemma":[0.007252244,0.001480077,0.001251099,0.001141011,0.001921381,0.001855322,0.002509258,0.002691573,0.0004703005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001419915,"about_ca_system_score_gemma":0.002511012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01451896,"about_ca_topic_score_gemma":0.01133713,"domain_scores_codex":[0.9985623,0.0006235498,0.00007754591,0.0001948705,0.0003684151,0.0001733993],"domain_scores_gemma":[0.9954939,0.003587932,0.000245918,0.0001231267,0.0003709928,0.00017821],"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":[0.00003039497,0.00002420079,0.0001319917,0.00005347247,0.0000209133,0.00002979542,0.0000143173,0.9886214,0.0001181765,0.004096949,0.0005205195,0.006337977],"study_design_scores_gemma":[0.000003979513,0.000006042934,0.00001950666,0.000004051574,0.000001807996,0.000002450851,0.000002248695,0.9977164,0.00004971068,0.00209271,0.00009883595,0.00000215015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009763344,0.0005076728,0.9851629,0.0004109804,0.00009662388,0.00005335182,0.0001496778,0.0002457563,0.003609758],"genre_scores_gemma":[0.6542222,0.0006357508,0.3318166,0.0003786116,0.000241082,0.000476816,0.0005253507,0.0003333722,0.01137032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01451896,"threshold_uncertainty_score":0.02886891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009279259049224723,"score_gpt":0.2097658528886154,"score_spread":0.2004865938393907,"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."}}