{"id":"W6944914286","doi":"10.22008/fk2/eqp5qx","title":"SICEv2.3.2 Northern Arctic Canada snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023","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; Arctic ice pack; Snow; Cryosphere; Table (database)","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":[0.0008725551,0.001418784,0.0008088941,0.002566015,0.001580237,0.002370744,0.001914641,0.0006460496,0.03021445],"category_scores_gemma":[0.001372433,0.0005275023,0.0008960869,0.004213231,0.0002728236,0.001293496,0.00102567,0.001135871,0.01946775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004932124,"about_ca_system_score_gemma":0.01259519,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8347037,"about_ca_topic_score_gemma":0.8404362,"domain_scores_codex":[0.9993105,0.00003004293,0.00002592353,0.0001153916,0.0003809537,0.0001371244],"domain_scores_gemma":[0.9986485,0.00002699483,0.00004292299,0.00009812286,0.001100032,0.00008346819],"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":[0.0001999239,0.00004458375,0.01720012,0.0004004819,0.0001778192,0.00009184777,0.00013177,0.006404011,0.003007266,0.003020351,0.9292301,0.04009168],"study_design_scores_gemma":[0.0001237041,0.00001822629,0.03185844,0.0003579676,0.00009197328,0.0001169157,0.0003025052,0.01251039,0.003885404,0.001436248,0.9491602,0.0001380374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00722463,0.0005873546,0.006238697,0.0002374436,0.0002794585,0.0001392241,0.9348547,0.006933914,0.04350449],"genre_scores_gemma":[0.01607629,0.0004044884,0.01258895,0.0002019085,0.00003267852,0.0001574316,0.9576656,0.002229832,0.0106428],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1652963,"threshold_uncertainty_score":0.3325394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03593638171844962,"score_gpt":0.2361145072471622,"score_spread":0.2001781255287126,"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."}}