{"id":"W1984941793","doi":"10.4296/cwrj3303283","title":"Improved Technologies and Management Practices in Irrigation—Implications for Water Savings in Southern Alberta","year":2008,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Water resources management and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Water efficiency; Blueprint; Subsidy; Water conservation; Irrigation; Promotion (chess); Purchasing; Water use; Irrigation management; Natural resource economics; Commodity; Water resource management; Finance; Economics; Environmental science; Marketing; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006613246,0.0001769782,0.0001826555,0.0005528798,0.001303653,0.001610271,0.0005377277,0.0003161136,0.00168159],"category_scores_gemma":[0.001482448,0.0001009663,0.000165707,0.002471868,0.0008200141,0.0005216525,0.0007002071,0.0002828797,0.00007646802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02082824,"about_ca_system_score_gemma":0.01956403,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9445679,"about_ca_topic_score_gemma":0.9823914,"domain_scores_codex":[0.9993808,0.000111338,0.00001734149,0.0000493505,0.0002411683,0.000199909],"domain_scores_gemma":[0.9994435,0.0001145669,0.0001278457,0.0000222682,0.0001747992,0.0001170227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007565345,0.0005880072,0.6397628,0.0004234352,0.000121367,0.001747503,0.007674192,0.06020674,0.01718838,0.03034522,0.005170786,0.2360151],"study_design_scores_gemma":[0.00004409918,0.0001499426,0.9422705,0.0000853317,0.00004556096,0.0001175304,0.01370827,0.01156288,0.001624349,0.004248421,0.02609839,0.0000448792],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792972,0.0006798239,0.0006140947,0.001309458,0.000007333235,0.000030442,0.0001365144,0.00001763973,0.01790742],"genre_scores_gemma":[0.9948579,0.0006248987,0.0006654467,0.00007313917,0.000003158535,0.000006933979,0.00009764475,0.000003126447,0.003667686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05543214,"threshold_uncertainty_score":0.1511202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01749746952275635,"score_gpt":0.199321370159676,"score_spread":0.1818239006369197,"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."}}