{"id":"W2318958713","doi":"10.3390/rs8040294","title":"Multiyear Arctic Ice Classification Using ASCAT and SSMIS","year":2016,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sea ice; Special sensor microwave/imager; Sea ice concentration; Environmental science; Scatterometer; Climatology; Arctic; Remote sensing; Brightness temperature; Arctic ice pack; Meteorology; Sea ice thickness; Geology; Computer science; Wind speed; Microwave; Geography; Oceanography","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":[0.0004750872,0.0006046575,0.000311317,0.004436744,0.0003543512,0.0007578575,0.000339206,0.0002166397,0.002319055],"category_scores_gemma":[0.0008801746,0.0001497053,0.00061064,0.002403904,0.0001297681,0.0006700379,0.0004418024,0.0002960522,0.001507206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006821859,"about_ca_system_score_gemma":0.0008261147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05366491,"about_ca_topic_score_gemma":0.06886104,"domain_scores_codex":[0.999642,0.00002942023,0.00004408403,0.00008916778,0.0001439621,0.00005135782],"domain_scores_gemma":[0.9992852,0.00003072672,0.000145857,0.00008235013,0.0004002871,0.00005576592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007216173,0.0003212153,0.5322647,0.0003237244,0.0004049076,0.0004288766,0.0005168515,0.1169737,0.02006669,0.00170962,0.06064693,0.2656211],"study_design_scores_gemma":[0.00004981136,0.0000654703,0.7130136,0.0001153905,0.00007454849,0.00009823937,0.0005774855,0.2396375,0.007018749,0.0007676714,0.03849427,0.00008722371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7656897,0.0006078024,0.04605747,0.0001450421,0.0002780542,0.0006076216,0.1616579,0.0042121,0.02074438],"genre_scores_gemma":[0.7386525,0.0004489537,0.05583418,0.00005517656,0.00008625186,0.0003420989,0.1978467,0.0003201728,0.006413947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05366491,"threshold_uncertainty_score":0.1067051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02720726233199655,"score_gpt":0.2311225135081831,"score_spread":0.2039152511761865,"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."}}