{"id":"W4391301057","doi":"10.1016/j.agsy.2023.103846","title":"Assessing the impact on crop modelling of multi- and uni-variate climate model bias adjustments","year":2024,"lang":"en","type":"article","venue":"Agricultural Systems","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Goddard Space Flight Center; Irish Centre for High-End Computing; National Oceanic and Atmospheric Administration; Commonwealth Scientific and Industrial Research Organisation; Environment and Climate Change Canada; National Aeronautics and Space Administration","keywords":"Random variate; Econometrics; Computer science; Economics; Statistics; Mathematics","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":[0.006565011,0.0008398247,0.0005970402,0.0004412857,0.0004595772,0.001151937,0.001362083,0.001959285,0.001623821],"category_scores_gemma":[0.02893353,0.0005432125,0.001125135,0.0006975025,0.0004951349,0.001867377,0.001318742,0.001478287,0.0001982891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194209,"about_ca_system_score_gemma":0.001717352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03790277,"about_ca_topic_score_gemma":0.0239298,"domain_scores_codex":[0.9984474,0.0009457747,0.0001020753,0.0002333418,0.0001479246,0.0001235076],"domain_scores_gemma":[0.982191,0.01351893,0.000990016,0.001494113,0.001480032,0.0003259772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004857218,0.00008676322,0.02058083,0.00007199381,0.0002863223,0.00004542624,0.00004857544,0.9670447,0.002104476,0.001247343,0.0003170478,0.007680769],"study_design_scores_gemma":[0.000122429,0.00009365333,0.007658184,0.00001732989,0.00009802417,0.00001407648,0.00003478341,0.9877371,0.00258125,0.001127574,0.0004824151,0.00003317407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9605582,0.0003238213,0.0339075,0.0009365438,0.0001459394,0.00007021229,0.001146271,0.0004902447,0.002421316],"genre_scores_gemma":[0.9898776,0.00004878026,0.009152976,0.0001146206,0.0000171446,0.0000271912,0.000263285,0.0000826863,0.0004157562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03790277,"threshold_uncertainty_score":0.07536429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1859942369588763,"score_gpt":0.3311049569771261,"score_spread":0.1451107200182498,"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."}}