{"id":"W4411577401","doi":"10.5194/egusphere-2025-2653","title":"Historical Climate and Future Projection in the North Atlantic and Arctic: Insights from EC-Earth3 High-Resolution Simulations","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Geological Studies and Exploration","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"HORIZON EUROPE Climate, Energy and Mobility; HORIZON EUROPE Framework Programme; Vetenskapsrådet; Svenska Forskningsrådet Formas; European Commission","keywords":"Arctic; The arctic; Projection (relational algebra); Oceanography; Climatology; Resolution (logic); High resolution; Geography; Environmental science; Geology; Computer science; Remote sensing; Artificial intelligence; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00160766,0.0005295138,0.0005900225,0.0004702178,0.000394271,0.001203444,0.00101961,0.001034553,0.001592317],"category_scores_gemma":[0.002610035,0.0003358926,0.001143136,0.001262543,0.0003643967,0.001085615,0.000525237,0.0009264162,0.0002172994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052898,"about_ca_system_score_gemma":0.001366257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1120009,"about_ca_topic_score_gemma":0.07964594,"domain_scores_codex":[0.999694,0.0001147834,0.00002499804,0.00006984767,0.00004893566,0.00004745143],"domain_scores_gemma":[0.9991479,0.000346511,0.00007555036,0.0001502252,0.0001845445,0.00009531406],"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":[0.0001192556,0.0001004584,0.03378818,0.00005903257,0.0002136965,0.0001489933,0.00004743808,0.9563183,0.0007290902,0.002053532,0.00278701,0.003635033],"study_design_scores_gemma":[0.0001178867,0.00004001326,0.01882234,0.00002445164,0.00009083908,0.0000301639,0.0001002914,0.9761174,0.0007545868,0.0009738383,0.002885072,0.00004301944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728948,0.0003866368,0.005188928,0.0009369259,0.00009540835,0.00003035707,0.01221474,0.0003222557,0.007929784],"genre_scores_gemma":[0.983291,0.0002447195,0.00611949,0.0001481301,0.0000267806,0.00003799009,0.009487384,0.0001152106,0.0005293349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1120009,"threshold_uncertainty_score":0.222698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02371948625021391,"score_gpt":0.2102487683265705,"score_spread":0.1865292820763566,"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."}}