{"id":"W4406346804","doi":"10.54254/2755-2721/2025.20298","title":"Global Insights, Local Applications: Irrigation Technologies and Agricultural Drought Mitigation in the Canadian Prairies","year":2025,"lang":"en","type":"article","venue":"Applied and Computational Engineering","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Water scarcity; Agriculture; Irrigation; Water conservation; Food security; Water security; Water resources; Environmental science; Farm water; Water resource management; Irrigation statistics; Business; Agroforestry; Geography; Agronomy; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009010058,0.0004821134,0.0003896936,0.001677383,0.001854067,0.002702112,0.0005692437,0.0004031255,0.003615751],"category_scores_gemma":[0.001850672,0.0001286238,0.0003955616,0.006646328,0.001359882,0.0009905456,0.0009999074,0.0009587526,0.0001546754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02201214,"about_ca_system_score_gemma":0.05279056,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9698714,"about_ca_topic_score_gemma":0.9890485,"domain_scores_codex":[0.9995205,0.00006768887,0.00001931964,0.00006050787,0.0002044206,0.0001275293],"domain_scores_gemma":[0.9990695,0.0001650135,0.0000653959,0.00002625697,0.0005997008,0.00007422165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001137679,0.0000664196,0.03474585,0.009755274,0.000360797,0.001224267,0.01257169,0.01451082,0.004638326,0.07776413,0.06515072,0.779098],"study_design_scores_gemma":[0.00001510442,0.00007038043,0.122057,0.005127364,0.0004291392,0.0003176666,0.01853637,0.002005861,0.001506702,0.01038812,0.8394262,0.0001201617],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1155637,0.5628148,0.007236329,0.04988022,0.0009590346,0.000169182,0.004338793,0.000160205,0.2588776],"genre_scores_gemma":[0.4805251,0.4956939,0.005124934,0.00269937,0.0001255317,0.0000447065,0.0007759889,0.00003757531,0.01497302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0301286,"threshold_uncertainty_score":0.15971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004310542001014286,"score_gpt":0.1844025892895114,"score_spread":0.1800920472884971,"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."}}