{"id":"W1539212378","doi":"10.1002/9781118368909.ch12","title":"Remote sensing of lake and river ice","year":2014,"lang":"en","type":"other","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; University of Waterloo","funders":"Japan Aerospace Exploration Agency; Canadian Space Agency; National Oceanic and Atmospheric Administration; European Space Agency","keywords":"Sea ice; Cryosphere; Arctic ice pack; Arctic; Snow; Antarctic sea ice; Shelf ice; Ice stream; Geology; Remote sensing; Sea ice thickness; Environmental science; Climatology; Oceanography; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008037991,0.0001009368,0.0001744844,0.00005307771,0.00002267248,0.000006536342,0.00005409655,0.000107352,0.008653536],"category_scores_gemma":[0.00001284208,0.00007551096,0.00002460559,0.00003582662,0.0001435419,0.00001452885,0.000008323448,0.00007575703,0.0001451733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":3.718681e-7,"about_ca_system_score_gemma":0.00001316623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007156402,"about_ca_topic_score_gemma":0.02864114,"domain_scores_codex":[0.9995327,0.00002186367,0.00009078385,0.0001388694,0.0001017226,0.0001140331],"domain_scores_gemma":[0.9996807,0.0000601255,0.00008626465,0.0001169401,0.000008741046,0.00004721395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001404439,0.000002960875,0.0271519,0.0002993834,0.00008299682,0.00001668282,0.0002104512,0.00001501661,0.00000128211,0.0001666325,0.1035622,0.8684764],"study_design_scores_gemma":[0.0001797213,0.00004933281,0.01639169,0.000184512,0.00005315745,0.0000371008,0.00007457841,0.04094256,9.339624e-7,0.0007309492,0.9410952,0.0002602187],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007392188,0.00006722052,0.007904155,0.00005656383,0.0001745359,0.00005877455,0.00005252826,0.00003828508,0.9909087],"genre_scores_gemma":[0.03132696,0.0004405652,0.05798224,0.0004888725,0.0002751588,3.1383e-9,0.0001348507,0.00003987193,0.9093115],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8682162,"threshold_uncertainty_score":0.999455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006551501170325708,"score_gpt":0.1863658715309948,"score_spread":0.1798143703606691,"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."}}