{"id":"W2295085913","doi":"10.1002/2015gl066712","title":"Albedo feedback enhanced by smoother Arctic sea ice","year":2015,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; ArcticNet","keywords":"Sea ice; Melt pond; Arctic ice pack; Sea ice thickness; Ice-albedo feedback; Albedo (alchemy); Climatology; Environmental science; Arctic; Advanced very-high-resolution radiometer; Sea ice concentration; Antarctic sea ice; Geology; Arctic sea ice decline; Cryosphere; Drift ice; Atmospheric sciences; Oceanography; Satellite","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":[0.0002104488,0.0003952085,0.0002984085,0.0004392283,0.0002305461,0.0005060196,0.0001667218,0.0003254467,0.001179712],"category_scores_gemma":[0.0007769183,0.0002705965,0.0003873631,0.0002659101,0.0002310304,0.0003830575,0.0003407078,0.0003244687,0.0001839546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004658186,"about_ca_system_score_gemma":0.0002105532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01201287,"about_ca_topic_score_gemma":0.01120068,"domain_scores_codex":[0.9998904,0.00002060576,0.000005120446,0.00004028257,0.00002001202,0.00002355005],"domain_scores_gemma":[0.9997813,0.00006759795,0.00004187213,0.00002776896,0.00005172964,0.00002981971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006891959,0.0002181093,0.5287576,0.0001295456,0.0003307187,0.0008102393,0.0003377958,0.1243659,0.3023373,0.001073167,0.002936631,0.03801385],"study_design_scores_gemma":[0.00003321486,0.00003926543,0.8127294,0.000009875832,0.00005604872,0.00007446054,0.0001001938,0.178442,0.007019165,0.0004725241,0.000987557,0.00003638842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950373,0.00008915007,0.002303141,0.0001595944,0.00003842251,0.00000564431,0.0004461393,0.0002701847,0.00165042],"genre_scores_gemma":[0.9995171,0.0000178631,0.0002319691,0.00001446156,0.0000106582,0.00000116749,0.00009364053,0.00001669067,0.00009651354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01201287,"threshold_uncertainty_score":0.02388591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02964064845356034,"score_gpt":0.2767184641971897,"score_spread":0.2470778157436293,"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."}}