{"id":"W4395049945","doi":"10.3390/su16093523","title":"Influence of Regional Temperature Anomalies on Strawberry Yield: A Study Using Multivariate Copula Analysis","year":2024,"lang":"en","type":"article","venue":"Sustainability","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Copula (linguistics); Agriculture; Cropping; Econometrics; Crop yield; Climate change; Multivariate statistics; Agricultural productivity; Context (archaeology); Yield (engineering); Environmental science; Predictability; Vine copula; Economics; Statistics; Mathematics; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0009913429,0.0004310368,0.0004840365,0.0008032114,0.0002406966,0.0006686928,0.0003531402,0.0002539798,0.0006603647],"category_scores_gemma":[0.003826717,0.0002014236,0.0007743447,0.001119735,0.0001729922,0.0004841789,0.0003159459,0.0003103376,0.0001243325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003657478,"about_ca_system_score_gemma":0.0003167481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01625812,"about_ca_topic_score_gemma":0.01102904,"domain_scores_codex":[0.9995893,0.000145398,0.00001796555,0.0001147349,0.00007848797,0.0000540524],"domain_scores_gemma":[0.9974884,0.001473914,0.0004302269,0.0002244652,0.0002858649,0.00009718182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003279425,0.0001856659,0.8760523,0.00006449575,0.0007857027,0.0008149723,0.0004001017,0.09143011,0.006344984,0.0008458946,0.0006645423,0.02208332],"study_design_scores_gemma":[0.000006671854,0.0001367074,0.696378,0.000007663982,0.0001322819,0.0001471821,0.0002920951,0.3010972,0.001006792,0.000278162,0.0004914589,0.00002583436],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971129,0.00007212119,0.002226526,0.00002473331,0.000004344444,0.000007616169,0.0001409129,0.00002720591,0.0003835405],"genre_scores_gemma":[0.9992172,0.00004774908,0.0004967228,0.000002712449,0.000004139601,0.000003192555,0.0001414714,0.000009705653,0.00007710938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01625812,"threshold_uncertainty_score":0.032327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04145127004253289,"score_gpt":0.3168027639501147,"score_spread":0.2753514939075818,"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."}}