{"id":"W6944907950","doi":"10.22008/fk2/47qxb1","title":"SICEv3.0 Northern Arctic Canada 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); Sea ice; Arctic; Snow; Radiometry; AERONET; Arctic ice pack; Aerosol","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":[0.0008672316,0.001283839,0.0008580748,0.002549103,0.001440584,0.002102025,0.001911432,0.000599413,0.0353563],"category_scores_gemma":[0.00131783,0.0005056729,0.0008360118,0.00406817,0.000275759,0.001195041,0.001043393,0.0008917277,0.01694608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004167,"about_ca_system_score_gemma":0.0107735,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8260639,"about_ca_topic_score_gemma":0.8604851,"domain_scores_codex":[0.9992678,0.00003373343,0.00002801455,0.0001227161,0.000402701,0.000145071],"domain_scores_gemma":[0.9985532,0.00002819225,0.00004349643,0.0001229441,0.001173954,0.00007824229],"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":[0.0002034713,0.00003960233,0.01643269,0.0004001319,0.0001933113,0.0001002539,0.0001334137,0.005729833,0.003214286,0.002907025,0.9315062,0.03913992],"study_design_scores_gemma":[0.000133493,0.00001913613,0.03495212,0.0003676658,0.00008290459,0.0001052285,0.0003300463,0.01240145,0.003444366,0.001384348,0.9466396,0.0001396014],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008238288,0.0004818165,0.005738598,0.0001748839,0.0002643228,0.0001116037,0.9312343,0.005546525,0.04820967],"genre_scores_gemma":[0.02085542,0.000336329,0.01302531,0.0002489318,0.00003445996,0.000174798,0.9511492,0.001854535,0.01232101],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1739361,"threshold_uncertainty_score":0.3499208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402616011039857,"score_gpt":0.2224974163151724,"score_spread":0.1984712562047738,"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."}}