{"id":"W7065354882","doi":"","title":"Development of a Cloud-Based Dual-Objective Nonlinear Programming Model for Irrigation Water Allocation","year":2020,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Electrical and Electromagnetic Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Irrigation; Irrigation district; Cloud computing; Evapotranspiration; Fuzzy logic; Nonlinear programming; Irrigation management; Decision support system; Farm water; Conjunctive use","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007782919,0.0002365436,0.0002860592,0.0001252669,0.0001698193,0.00003571123,0.0001868004,0.0001258529,0.002101792],"category_scores_gemma":[0.00000381185,0.0002206915,0.000153771,0.0003084625,0.00002225514,0.00009063491,0.00002841754,0.0002316091,0.00001489691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001096621,"about_ca_system_score_gemma":0.0004688625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004159833,"about_ca_topic_score_gemma":0.00005621677,"domain_scores_codex":[0.998695,0.00003758465,0.0002664739,0.000387577,0.0002594024,0.0003540218],"domain_scores_gemma":[0.9993046,0.0000315478,0.0001548664,0.0001107585,0.0003011271,0.00009709087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001106369,0.0003609715,0.00009205503,0.0005842931,0.0003309003,0.000002391937,0.004982906,0.001131825,0.02971416,0.003908331,0.000148554,0.9576373],"study_design_scores_gemma":[0.003361061,0.000687118,0.00008460274,0.0002355389,0.0003777264,1.736106e-7,0.003789402,0.3953505,0.4622696,0.001927152,0.1309303,0.0009867691],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1625378,0.0000501918,0.5217602,0.000360297,0.0002736012,0.004742038,0.0001149522,0.0001623022,0.3099986],"genre_scores_gemma":[0.3845391,0.000001397845,0.09355521,0.0000274079,0.0003053763,0.00008008353,0.008137324,0.0001030681,0.513251],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9566505,"threshold_uncertainty_score":0.9988104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636160038190082,"score_gpt":0.2376868700024729,"score_spread":0.2213252696205721,"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."}}