{"id":"W4385456246","doi":"10.1080/07055900.2023.2239194","title":"An Approach for Selecting Observationally-Constrained Global Climate Model Ensembles for Regional Climate Impacts and Adaptation Studies in Canada","year":2023,"lang":"en","type":"article","venue":"ATMOSPHERE-OCEAN","topic":"Climate variability and models","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Coupled model intercomparison project; Climatology; Climate model; Environmental science; Precipitation; Climate change; Global warming; General Circulation Model; GCM transcription factors; Econometrics; Meteorology; Geography; Mathematics; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007841128,0.0001847151,0.000237803,0.00000391309,0.0002926207,0.00003395656,0.0001269193,0.0000623493,0.000005699134],"category_scores_gemma":[0.0001447281,0.0001812694,0.00004278707,0.0002894062,0.00009541514,0.000352053,0.0000824475,0.00005712626,8.147687e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006826725,"about_ca_system_score_gemma":0.0001981425,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05859505,"about_ca_topic_score_gemma":0.4418875,"domain_scores_codex":[0.9983148,0.00003803192,0.0003744127,0.00047552,0.000227689,0.0005695419],"domain_scores_gemma":[0.9992836,0.0002924491,0.0001213246,0.0001477988,0.00004065812,0.0001141588],"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":[0.0001455752,0.00004405272,0.1516624,0.0001766196,0.00002028541,8.85723e-7,0.0009343527,0.842753,0.0002052511,0.002530787,0.0005392389,0.0009875674],"study_design_scores_gemma":[0.0006749997,0.00005505969,0.02632558,0.00002556847,0.00001933299,0.000003924839,0.003899954,0.9617696,0.000009450155,0.006991274,0.00002668518,0.0001985203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935069,0.00004398398,0.004918262,0.0002662895,0.00004478679,0.000692368,0.0002796676,0.0000628931,0.0001848258],"genre_scores_gemma":[0.9363399,0.0001307419,0.06290979,0.0002883598,0.00002488811,0.00005520718,0.000221741,0.00001827295,0.0000110913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3832924,"threshold_uncertainty_score":0.9476739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.091529397263892,"score_gpt":0.2988265937019652,"score_spread":0.2072971964380732,"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."}}