{"id":"W3114339836","doi":"10.1175/jcli-d-20-0178.1","title":"Decomposing the Drivers of Polar Amplification with a Single-Column Model","year":2020,"lang":"en","type":"article","venue":"Journal of Climate","topic":"Climate variability and models","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Langley Research Center; Compute Canada; National Science Foundation","keywords":"Forcing (mathematics); Polar; Environmental science; Climatology; Atmospheric sciences; Arctic; Atmosphere (unit); Latitude; Global warming; Climate change; Geology; Meteorology; Oceanography; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003037899,0.0008555737,0.0006201566,0.0003866042,0.0004619536,0.001150467,0.001179947,0.001035258,0.002446485],"category_scores_gemma":[0.0009608603,0.0005585771,0.001075874,0.0004001292,0.0005065753,0.001093387,0.000673436,0.0008717439,0.0002235231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009993217,"about_ca_system_score_gemma":0.001330833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05266204,"about_ca_topic_score_gemma":0.02309335,"domain_scores_codex":[0.9999044,0.00002755007,0.000004998009,0.00002392941,0.00001321241,0.00002593041],"domain_scores_gemma":[0.9995887,0.0001589903,0.00006972092,0.00004251546,0.00006638291,0.00007377943],"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":[0.00005594938,0.00002815628,0.003911383,0.0000188927,0.00006013854,0.00004800373,0.00001335568,0.9902585,0.002023495,0.001880892,0.0002537482,0.001447568],"study_design_scores_gemma":[0.00001106403,0.00000726566,0.0005608201,0.000001464627,0.0000129558,0.000003066918,0.000005011568,0.9986776,0.0001208336,0.0005023368,0.00009204687,0.000005557806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8889664,0.0003795569,0.09830806,0.001003168,0.0001851567,0.000101888,0.001632429,0.0007604533,0.00866284],"genre_scores_gemma":[0.9914343,0.0001595351,0.006274318,0.00009324673,0.00006179754,0.00005828385,0.0002736555,0.00007519723,0.001569622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05266204,"threshold_uncertainty_score":0.1047111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03185768066130944,"score_gpt":0.2391261027176786,"score_spread":0.2072684220563691,"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."}}