{"id":"W6907490835","doi":"10.22008/fk2/rtfm0k","title":"SICEv3.0 Alaska and Yukon snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)","year":2023,"lang":"en","type":"dataset","venue":"Geological Survey of Denmark and Greenland (GEUS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Albedo (alchemy); Snow; Sea ice; Arctic; Radiometry; AERONET; Aerosol; Arctic ice pack","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":[0.0005170058,0.000757873,0.0005589962,0.001699538,0.000488769,0.00107453,0.001121284,0.000550014,0.02268715],"category_scores_gemma":[0.0007236945,0.000373338,0.0006501703,0.002671973,0.0001747863,0.001255511,0.0007231544,0.0005536658,0.01367128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005302813,"about_ca_system_score_gemma":0.001407383,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08149145,"about_ca_topic_score_gemma":0.1161554,"domain_scores_codex":[0.9996921,0.00002140081,0.00002770855,0.00008189744,0.0001230496,0.00005382298],"domain_scores_gemma":[0.9994971,0.00001814416,0.00003360841,0.0001039372,0.0003198518,0.00002742853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003214587,0.0001155533,0.06058509,0.0009066125,0.0004329017,0.0002480087,0.0002658026,0.0105022,0.00876925,0.003137355,0.8555323,0.05918355],"study_design_scores_gemma":[0.0001650386,0.00004804275,0.1206515,0.0003772507,0.000180982,0.0002635478,0.0006125287,0.01677795,0.00623241,0.002360499,0.8521832,0.000147032],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02851686,0.0003740553,0.005507018,0.0001133047,0.000189704,0.0001128258,0.9307352,0.004576094,0.02987492],"genre_scores_gemma":[0.03513419,0.0001473882,0.008204538,0.0001489702,0.00001975405,0.0001547398,0.9497539,0.0009252958,0.00551118],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9185085,"threshold_uncertainty_score":0.1620342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03191815478150759,"score_gpt":0.2456717672470966,"score_spread":0.213753612465589,"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."}}