{"id":"W4280630276","doi":"10.1175/jcli-d-21-0811.1","title":"Multi-Model Forecast Quality Assessment of CMIP6 Decadal Predictions","year":2022,"lang":"en","type":"article","venue":"Journal of Climate","topic":"Climate variability and models","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos","funders":"Horizon 2020 Framework Programme; European Centre for Medium-Range Weather Forecasts; European Commission; H2020 Marie Skłodowska-Curie Actions; “la Caixa” Foundation","keywords":"Coupled model intercomparison project; Initialization; Climatology; Precipitation; Forecast skill; Environmental science; Climate model; Quality (philosophy); Computer science; Ensemble forecasting; Meteorology; Climate change; Geography; Machine learning; Geology","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":[0.006774462,0.0006486801,0.000530644,0.001146354,0.0003041188,0.001028101,0.0006392776,0.000700016,0.001040223],"category_scores_gemma":[0.01278916,0.0003156436,0.0008332049,0.0008007266,0.0002369556,0.0009761666,0.0006647909,0.0007734096,0.0002401134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008022063,"about_ca_system_score_gemma":0.0006770248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02222793,"about_ca_topic_score_gemma":0.01015144,"domain_scores_codex":[0.9989042,0.0004004264,0.0001308282,0.0002244771,0.0002612679,0.00007871648],"domain_scores_gemma":[0.9925929,0.003665884,0.0007943062,0.0006979717,0.001975501,0.000273514],"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":[0.0007106471,0.0001119195,0.1009964,0.0001084508,0.0005077148,0.00008493882,0.00006366794,0.864606,0.002221605,0.0004389876,0.002289392,0.02786036],"study_design_scores_gemma":[0.00004458031,0.0001048197,0.03927291,0.00002706099,0.00006863222,0.00001923314,0.00004213109,0.9568491,0.002527737,0.0002860846,0.0007281215,0.00002947385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618183,0.0008788758,0.0259031,0.0006880986,0.0002286573,0.00008337857,0.006716533,0.001057791,0.002625262],"genre_scores_gemma":[0.9880436,0.0001236366,0.006206782,0.00004841203,0.00003275594,0.00002245658,0.00515454,0.00007076011,0.0002971051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02222793,"threshold_uncertainty_score":0.04419708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06981979827860825,"score_gpt":0.3561534018987703,"score_spread":0.2863336036201621,"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."}}