{"id":"W4364356009","doi":"10.1088/2752-5295/accbe3","title":"Variability modes of September Arctic sea ice: drivers and their contributions to sea ice trend and extremes","year":2023,"lang":"en","type":"article","venue":"Environmental Research Climate","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Svenska Forskningsrådet Formas","keywords":"Sea ice; Arctic sea ice decline; Arctic ice pack; Climatology; Arctic; Arctic oscillation; Sea ice concentration; Environmental science; Arctic geoengineering; Oceanography; Drift ice; Arctic dipole anomaly; Antarctic sea ice; Cryosphere; North Atlantic oscillation; Geology; Sea ice thickness; Northern Hemisphere","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":[0.001606919,0.0001406735,0.0001946987,0.0001211313,0.0004403022,0.00004166363,0.00014211,0.00006412867,0.000945433],"category_scores_gemma":[0.0001672606,0.0001125846,0.00004118674,0.0002569285,0.0006446885,0.000197069,0.0001750743,0.0002406529,0.0001784628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003754776,"about_ca_system_score_gemma":0.00002375193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004522413,"about_ca_topic_score_gemma":0.0005087653,"domain_scores_codex":[0.9981461,0.0002812396,0.0001961593,0.0003693822,0.0004081895,0.0005989694],"domain_scores_gemma":[0.9983819,0.001051633,0.00003707723,0.0002132714,0.00001516562,0.0003009522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008038238,0.0000428948,0.9880443,0.00007811076,0.00003296399,0.00001004375,0.0009399831,0.0004599316,0.001170607,0.0001141439,0.000144526,0.008882135],"study_design_scores_gemma":[0.0003485664,0.0001879385,0.9496543,0.0000345457,0.0000143963,0.00001084165,0.005014413,0.04132412,0.0002019745,0.001915217,0.001139607,0.00015404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942952,0.00007770534,0.00005684074,0.0005070581,0.00003233559,0.0002802226,0.002725651,0.00002400965,0.002000932],"genre_scores_gemma":[0.997903,0.001278777,0.0001800045,0.00004316753,0.00002536539,0.000004900262,0.0003058463,0.000005947597,0.0002529676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04086419,"threshold_uncertainty_score":0.9999678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02350252366900654,"score_gpt":0.288424216260919,"score_spread":0.2649216925919125,"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."}}