{"id":"W2026413132","doi":"10.1175/2009jcli3060.1","title":"A U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results","year":2009,"lang":"en","type":"article","venue":"Journal of Climate","topic":"Climate variability and models","field":"Environmental Science","cited_by":282,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Lamont-Doherty Earth Observatory, Columbia University; University of Miami; National Aeronautics and Space Administration; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Climatology; Forcing (mathematics); Predictability; Precipitation; Environmental science; Atlantic multidecadal oscillation; Sea surface temperature; Anomaly (physics); Pacific decadal oscillation; Climate model; Forecast skill; Climate change; Geology; Meteorology; Geography; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03043535,0.00305284,0.001410137,0.004386402,0.000598282,0.001844279,0.002344134,0.001059819,0.002041578],"category_scores_gemma":[0.01291032,0.0007791132,0.001848619,0.003872651,0.0005794441,0.001600525,0.002812435,0.00129861,0.0008509747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001371681,"about_ca_system_score_gemma":0.002191296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02127437,"about_ca_topic_score_gemma":0.008769222,"domain_scores_codex":[0.9893292,0.006818555,0.000469064,0.0009551426,0.0019422,0.0004858741],"domain_scores_gemma":[0.9891071,0.003725078,0.0009297237,0.002182857,0.00288017,0.001175054],"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":[0.004567397,0.005356119,0.1510638,0.002705012,0.005399561,0.0002672492,0.0007427845,0.3840531,0.02390617,0.01406298,0.1183691,0.2895068],"study_design_scores_gemma":[0.003993256,0.008573622,0.2500513,0.001192918,0.001387725,0.0002174846,0.000971229,0.5836419,0.04012499,0.006451977,0.1028583,0.0005353155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5490955,0.01511062,0.08671121,0.003019667,0.0005489038,0.009163053,0.2879804,0.01358145,0.03478923],"genre_scores_gemma":[0.4646516,0.004902487,0.2254349,0.0007608694,0.000237589,0.007059978,0.288252,0.003491371,0.005209242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03043535,"threshold_uncertainty_score":0.1609595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08027107466880738,"score_gpt":0.3388222457269344,"score_spread":0.258551171058127,"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."}}