{"id":"W4396624746","doi":"10.3390/atmos15050567","title":"Why Does the Ensemble Mean of CMIP6 Models Simulate Arctic Temperature More Accurately Than Global Temperature?","year":2024,"lang":"en","type":"article","venue":"Atmosphere","topic":"Climate variability and models","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"NOAA Pacific Marine Environmental Laboratory; Global Ocean Monitoring and Observing Program; National Oceanic and Atmospheric Administration","keywords":"Climatology; Mean radiant temperature; Environmental science; The arctic; Meteorology; Data assimilation; Atmospheric sciences; Climate change; Geology; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000309038,0.0002958532,0.0002633628,0.000002090288,0.0002292017,0.0001876136,0.0005009295,0.0002221387,0.001340554],"category_scores_gemma":[0.00003331298,0.0001625041,0.0001921711,0.0005178209,0.0002926395,0.0005288605,0.000293327,0.0003433938,0.00008800179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001889145,"about_ca_system_score_gemma":0.000038355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002515682,"about_ca_topic_score_gemma":0.002350447,"domain_scores_codex":[0.9981259,0.0001041021,0.0003235227,0.0005809077,0.0004513903,0.0004142505],"domain_scores_gemma":[0.9989602,0.000160479,0.00005930035,0.0006756387,0.00002748796,0.0001169],"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":[0.0001491193,0.0002676595,0.0097504,0.000414308,0.0002185594,0.00008153057,0.007367994,0.9182558,0.03344978,0.01034529,0.01682482,0.002874749],"study_design_scores_gemma":[0.001329755,0.0003450343,0.009762798,0.0008944201,0.0004770012,0.0001465361,0.004742299,0.7343927,0.01383456,0.2035641,0.02870334,0.00180748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902768,0.0006359432,0.0001064666,0.003397618,0.0004006519,0.0004058197,0.00009101834,0.000129162,0.004556481],"genre_scores_gemma":[0.9973008,0.0001163453,0.0004541937,0.001062682,0.00007394973,0.00002017542,0.00001486313,0.00002824513,0.00092876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1932188,"threshold_uncertainty_score":0.9995723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714594925833296,"score_gpt":0.2591954223668227,"score_spread":0.2420494731084898,"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."}}