{"id":"W6907509047","doi":"10.22008/fk2/1kmrcc","title":"SICEv3.0 Southern 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; Arctic ice pack; Radiometry; AERONET; 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":[0.0008586797,0.001245321,0.0008389765,0.002587933,0.001459798,0.002130376,0.001825679,0.0005924914,0.03547729],"category_scores_gemma":[0.001298684,0.0004835968,0.0008294656,0.004051272,0.0002736022,0.001167867,0.00103573,0.0008878249,0.01650102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004034041,"about_ca_system_score_gemma":0.01124601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8235837,"about_ca_topic_score_gemma":0.8548787,"domain_scores_codex":[0.9992827,0.00003354066,0.00002840401,0.0001227652,0.0003888404,0.0001438809],"domain_scores_gemma":[0.9985195,0.00002776461,0.00004483842,0.0001242032,0.001202299,0.00008138368],"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":[0.0002087616,0.00004054117,0.01724124,0.0004094281,0.0002018765,0.0001049322,0.000139603,0.005554956,0.003286722,0.003144834,0.9287724,0.04089465],"study_design_scores_gemma":[0.0001377666,0.00001921211,0.03609314,0.0003683867,0.0000837259,0.0001043169,0.0003317358,0.01166396,0.00323619,0.001420331,0.9464074,0.0001338872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008604793,0.0005069612,0.005743458,0.0001905877,0.0002842344,0.0001120312,0.9272926,0.005620809,0.05164453],"genre_scores_gemma":[0.02179484,0.0003545882,0.01326156,0.0002667887,0.00003750743,0.0001695376,0.949577,0.001840698,0.01269743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1764163,"threshold_uncertainty_score":0.3549104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.025310809960191,"score_gpt":0.2229540213116258,"score_spread":0.1976432113514348,"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."}}