{"id":"W4390740994","doi":"10.1038/s41597-023-02855-z","title":"An ensemble of bias-adjusted CMIP6 climate simulations based on a high-resolution North American reanalysis","year":2024,"lang":"en","type":"article","venue":"Scientific Data","topic":"Climate variability and models","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos","funders":"Environment and Climate Change Canada","keywords":"Quantile; Climate model; Coupled model intercomparison project; Climatology; Climate change; Computer science; Environmental science; Multivariate statistics; Precipitation; Econometrics; Statistics; Meteorology; Mathematics; Machine learning; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001362621,0.0001230254,0.0001744006,0.0001877913,0.0002719817,0.000215582,0.0007690153,0.0000269061,0.0009234043],"category_scores_gemma":[0.0001598206,0.0001076622,0.00005204474,0.002121595,0.0005661803,0.0005692722,0.0003753201,0.00009256932,0.0003028855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001031818,"about_ca_system_score_gemma":0.00003814109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001975965,"about_ca_topic_score_gemma":0.01028732,"domain_scores_codex":[0.9976977,0.0001432302,0.000314635,0.000969725,0.0005756869,0.0002990999],"domain_scores_gemma":[0.9970594,0.0001897679,0.00009465026,0.002520134,0.00001918901,0.0001168629],"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":[0.00004227146,0.0005190581,0.02201171,0.00005540474,0.00002215378,0.000005244542,0.0002567105,0.9394712,0.01560664,0.0002837919,0.006500234,0.01522551],"study_design_scores_gemma":[0.00008078831,0.00006011005,0.02594488,0.00001983679,0.00008013337,2.783805e-7,0.00003576756,0.9696714,0.0002825985,0.0001149636,0.003588893,0.0001202945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820929,0.00000586618,0.005842308,0.0002468152,0.0003205344,0.0001892201,0.01063161,0.0001059468,0.0005647598],"genre_scores_gemma":[0.9882349,0.000003833461,0.002713285,0.00004621204,0.00001728261,0.000003841916,0.008857919,0.00001169889,0.0001110491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03020019,"threshold_uncertainty_score":0.9999899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07410897584124482,"score_gpt":0.3027905452355045,"score_spread":0.2286815693942597,"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."}}