{"id":"W2223430424","doi":"10.3394/0380-1330(2007)33[722:ssrsog]2.0.co;2","title":"Satellite SAR Remote Sensing of Great Lakes Ice Cover, Part 1. Ice Backscatter Signatures at C Band","year":2007,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Jet Propulsion Laboratory; National Oceanic and Atmospheric Administration","keywords":"Remote sensing; Sea ice; Backscatter (email); Synthetic aperture radar; Scatterometer; Geology; Radar; Snow; Sea ice thickness; Polarimetry; Satellite; Open water; Sea ice concentration; Arctic ice pack; Environmental science; Meteorology; Wind speed; Oceanography; Geography; Geomorphology; Scattering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.00009468365,0.0002438924,0.0001298626,0.0005111193,0.0001323613,0.0001866845,0.0001076791,0.0001311104,0.001374442],"category_scores_gemma":[0.0001781233,0.0001669988,0.0001707124,0.0005216485,0.0001030919,0.0001531963,0.0001366115,0.00006796331,0.0003360081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001880399,"about_ca_system_score_gemma":0.0002793193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03170183,"about_ca_topic_score_gemma":0.06599125,"domain_scores_codex":[0.9999712,0.000005566533,0.000002392351,0.000005425159,0.00001065879,0.000004850358],"domain_scores_gemma":[0.9999276,0.00001419203,0.00001319848,0.000009099039,0.00002412023,0.00001175024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001017196,0.0003586823,0.7087393,0.0002481112,0.0003101029,0.0002730603,0.0003426626,0.0117866,0.1532628,0.0004686198,0.009763449,0.1134292],"study_design_scores_gemma":[0.00001820722,0.00004513285,0.9944634,0.000005769489,0.00002714892,0.00004908881,0.00003680079,0.001788572,0.002557728,0.00002722634,0.000977612,0.000003442114],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994134,0.0002456732,0.0003322035,0.00004959256,0.000005910262,0.00001577416,0.002302327,0.00002533022,0.002889317],"genre_scores_gemma":[0.9887125,0.0003838908,0.001442269,0.00005230584,0.0000137924,0.00002239673,0.005753323,0.00001289142,0.003606602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9682982,"threshold_uncertainty_score":0.06303459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03424231724055606,"score_gpt":0.2951008958478597,"score_spread":0.2608585786073037,"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."}}