{"id":"W4226226735","doi":"10.3390/su14074241","title":"Impact of Climate Change on Productivity and Technical Efficiency in Canadian Crop Production","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Inefficiency; Climate change; Productivity; Frontier; Environmental science; Precipitation; Index (typography); Production (economics); Climatology; Agricultural productivity; Production–possibility frontier; Agriculture; Stochastic frontier analysis; Food security; Climate model; Growing season; Econometrics; Panel data; Economics; Meteorology; Geography; Ecology; Computer science","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":[0.001292975,0.0003130352,0.0003025499,0.0009914256,0.0006457323,0.001447594,0.0004364517,0.0002141996,0.001561979],"category_scores_gemma":[0.003941594,0.0001453036,0.0006585951,0.002299507,0.0006132939,0.0004606553,0.000525885,0.0004521967,0.0001051649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01921201,"about_ca_system_score_gemma":0.01568972,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9592355,"about_ca_topic_score_gemma":0.9687713,"domain_scores_codex":[0.999299,0.00008122135,0.00002912297,0.0001133092,0.0002379278,0.0002394911],"domain_scores_gemma":[0.9986055,0.0004524179,0.0002202944,0.000111756,0.0004784952,0.0001313854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001978796,0.00006543486,0.731392,0.00009427689,0.0003044544,0.0002045943,0.0004127663,0.2273628,0.001777587,0.007742067,0.001669452,0.02877676],"study_design_scores_gemma":[0.000009541654,0.00002550534,0.8878434,0.00001676722,0.00006220374,0.00003224334,0.0005133571,0.1062542,0.0007302572,0.001200037,0.003282134,0.00003031241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907033,0.0003258807,0.001812229,0.0002434984,0.000004261813,0.00001527644,0.00297703,0.00002857347,0.003889982],"genre_scores_gemma":[0.9975474,0.0001661255,0.0005496531,0.000009650581,0.00000140652,0.000003767383,0.001089745,0.000004498097,0.0006276951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04076445,"threshold_uncertainty_score":0.1393935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03957878442797671,"score_gpt":0.3845859204851248,"score_spread":0.3450071360571481,"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."}}