{"id":"W2920628506","doi":"10.1038/s41467-019-08745-6","title":"State-of-the-art global models underestimate impacts from climate extremes","year":2019,"lang":"en","type":"article","venue":"Nature Communications","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":317,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; McGill University; Université du Québec à Montréal; Dalhousie University","funders":"Japan Society for the Promotion of Science; Leibniz-Gemeinschaft; Bundesministerium für Bildung und Forschung; Grains Research and Development Corporation","keywords":"Climate change; Hydropower; Environmental science; Impact assessment; Climate model; Economic impact analysis; Ecosystem; Environmental resource management; Agriculture; Natural resource economics; Climatology; Ecology; Economics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001797562,0.000128396,0.0001631141,0.00001514182,0.0002142837,0.00002759907,0.001216742,0.0001342627,0.0004235786],"category_scores_gemma":[0.00005126214,0.00009743204,0.00006968505,0.0003208896,0.000161519,0.0002771989,0.001107045,0.0004191808,0.0006832748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000224261,"about_ca_system_score_gemma":0.0000292242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004625074,"about_ca_topic_score_gemma":0.006941261,"domain_scores_codex":[0.9988781,0.00009423307,0.0002491597,0.0001793299,0.0002675559,0.0003315914],"domain_scores_gemma":[0.9975262,0.0001677453,0.0001775818,0.001983934,0.00001578573,0.0001287113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007196481,0.0004068206,0.917864,0.00005110185,0.0000379858,7.538507e-7,0.001560584,0.003221567,0.0053069,0.005873445,0.05660767,0.008997234],"study_design_scores_gemma":[0.0006738123,0.00005554798,0.9057008,0.0002094648,0.00004564113,0.000005471502,0.0001382276,0.02466659,0.0005054694,0.04354958,0.02412015,0.0003292391],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9286862,0.003095531,0.000054723,0.00940425,0.0003251989,0.0006115338,0.0006407634,0.00007436053,0.05710747],"genre_scores_gemma":[0.9944335,0.001456192,0.002586659,0.001297176,0.000009225497,0.00000908367,0.00008723857,0.00001249053,0.0001084531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06574731,"threshold_uncertainty_score":0.8782343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05881624723844471,"score_gpt":0.3427029663717537,"score_spread":0.283886719133309,"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."}}