{"id":"W4402389426","doi":"10.1016/j.compag.2024.109230","title":"Sensitivity study of the Predictive Optimal Water and Energy Irrigation (POWEIr) controller’s schedules for sustainable agriculture systems in resource-constrained contexts","year":2024,"lang":"en","type":"article","venue":"Computers and Electronics in Agriculture","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Alberta; United States Agency for International Development; Julia Burke Foundation","keywords":"Resource (disambiguation); Sensitivity (control systems); Agriculture; Irrigation; Agricultural engineering; Controller (irrigation); Model predictive control; Environmental science; Water resource management; Computer science; Environmental resource management; Engineering; Control (management); Agronomy; Geography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003277633,0.0002161508,0.000311701,0.00004321669,0.0001720591,0.00008649373,0.0001037524,0.0001202274,5.976306e-7],"category_scores_gemma":[0.000012849,0.0001045293,0.00004545449,0.0002340764,0.0001295685,0.0001616565,0.0002471237,0.0002145129,1.200413e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002329911,"about_ca_system_score_gemma":0.00001121748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008199828,"about_ca_topic_score_gemma":0.002375958,"domain_scores_codex":[0.9985467,0.0001800619,0.0002521109,0.0004215553,0.0001766882,0.0004229502],"domain_scores_gemma":[0.9996508,0.0001287174,0.00005539829,0.00009118105,0.00003202467,0.00004190834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001211346,0.002171309,0.01001097,0.0008854604,0.001267476,0.0002934593,0.03978892,0.369337,0.09467894,0.4498369,0.02250744,0.008010788],"study_design_scores_gemma":[0.02266149,0.009740286,0.1715747,0.002001756,0.0007435975,0.000572407,0.1139621,0.4956219,0.02518612,0.06046679,0.09392895,0.003539969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920822,0.004053844,0.001213474,0.0006505798,0.0001153344,0.000929929,0.00002156718,0.00003895261,0.0008941638],"genre_scores_gemma":[0.9993032,0.00002581077,0.00004001602,0.0000417392,0.0000514567,0.00009722309,0.00001447487,0.00000831756,0.0004177421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3893701,"threshold_uncertainty_score":0.4262579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003418256708406655,"score_gpt":0.180755563826905,"score_spread":0.1773373071184984,"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."}}