{"id":"W2939759448","doi":"10.1088/1748-9326/ab17fb","title":"Climate change impacts on Canadian yields of spring wheat, canola and maize for global warming levels of 1.5 °C, 2.0 °C, 2.5 °C and 3.0 °C","year":2019,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"DSSAT; Global warming; Environmental science; Climate change; Canola; Agronomy; Crop yield; Coupled model intercomparison project; Cropping; Agriculture; Crop; Yield (engineering); Atmospheric sciences; Climate model; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004373763,0.0001353432,0.0001962497,0.00003276532,0.0001219981,0.00003214703,0.0001431938,0.00009035406,0.0001451847],"category_scores_gemma":[0.00004126196,0.00006186956,0.00004427168,0.0001218661,0.0001492614,0.0001347012,0.0001277723,0.0001360874,0.000007057581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002031977,"about_ca_system_score_gemma":0.000005084843,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01767368,"about_ca_topic_score_gemma":0.0291362,"domain_scores_codex":[0.9985499,0.00006059991,0.0001570104,0.0002804899,0.0003362397,0.000615792],"domain_scores_gemma":[0.9993191,0.0002373625,0.00005963089,0.00006817377,0.00000942138,0.0003063393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005462067,0.00003040839,0.1914446,0.00005973072,0.00001042688,0.000004457913,0.0002120526,7.860758e-7,0.7822499,0.0000449564,0.0001019225,0.02578617],"study_design_scores_gemma":[0.0002634602,0.0004729425,0.9822857,0.0001348536,0.000005027035,0.00000595737,0.0007705299,0.00001716643,0.0151964,0.00001917835,0.0007035533,0.000125274],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934109,0.0002630672,7.597178e-8,0.004430622,0.00003291394,0.0006822216,0.00100659,0.000005609583,0.0001679409],"genre_scores_gemma":[0.9989576,0.0003758929,0.0000297969,0.0005076166,0.00007221686,0.00001836781,0.00001884539,0.000002048417,0.00001762068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7908411,"threshold_uncertainty_score":0.9888677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08351798748163389,"score_gpt":0.3005404037326461,"score_spread":0.2170224162510122,"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."}}