{"id":"W4285288199","doi":"10.1525/elementa.2020.00080","title":"A method to derive satellite PAR albedo time series over first-year sea ice in the Arctic Ocean","year":2022,"lang":"en","type":"article","venue":"Elementa Science of the Anthropocene","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Albedo (alchemy); Environmental science; Sea ice; Moderate-resolution imaging spectroradiometer; Snow; Satellite; Remote sensing; Arctic; Climatology; Arctic ice pack; Cryosphere; Meteorology; Atmospheric sciences; Geology; Geography; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004031799,0.0007404636,0.000288517,0.001184167,0.0004415599,0.00048159,0.0004640564,0.0002897788,0.0006611594],"category_scores_gemma":[0.001515647,0.000367861,0.0005463949,0.001306275,0.0001369234,0.0004833252,0.0002573605,0.0006113292,0.0004636098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004673811,"about_ca_system_score_gemma":0.000822015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02825636,"about_ca_topic_score_gemma":0.02622672,"domain_scores_codex":[0.9998015,0.00002260627,0.00001310191,0.00008450043,0.00006569375,0.00001263744],"domain_scores_gemma":[0.9996685,0.000056435,0.00007546123,0.00006158154,0.000126354,0.00001172009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009418691,0.0001495259,0.08340109,0.0002169099,0.0003275632,0.0001786982,0.0002521267,0.2360991,0.03694109,0.002958799,0.004266268,0.6351146],"study_design_scores_gemma":[0.00001808439,0.0000487547,0.07034813,0.00002269495,0.00004583418,0.0002025785,0.00005333841,0.9077239,0.01410599,0.001455501,0.005913474,0.00006175409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1217771,0.0002741732,0.8687664,0.00008801444,0.00008272134,0.0001315043,0.002832527,0.003839822,0.002207854],"genre_scores_gemma":[0.4913742,0.00029547,0.5028831,0.0000365497,0.00005054409,0.0002841681,0.003453252,0.0002555001,0.001367237],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02825636,"threshold_uncertainty_score":0.05618376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008005737634666167,"score_gpt":0.2455824278018506,"score_spread":0.2375766901671845,"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."}}