{"id":"W4205934717","doi":"10.3390/rs14020301","title":"The RADARSAT Constellation Mission Core Applications: First Results","year":2022,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Institut National de la Recherche Scientifique; Centre For Cold Ocean Resources Engineering; Natural Resources Canada; Environment and Climate Change Canada","funders":"","keywords":"Remote sensing; Synthetic aperture radar; Sea ice; Constellation; Environmental science; Arctic; Geology; Climatology; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.000387819,0.00006977034,0.00006449122,0.00002378507,0.002139739,0.0000387428,0.0001002378,0.0000211176,0.00006059456],"category_scores_gemma":[0.00003827695,0.00005162102,0.00003361745,0.000176053,0.00007758653,0.00003869057,0.00002294503,0.000163211,0.00003512429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001583953,"about_ca_system_score_gemma":0.00004473107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008092578,"about_ca_topic_score_gemma":0.0001337972,"domain_scores_codex":[0.9991879,0.00005664135,0.0001790266,0.0001647008,0.0002373386,0.0001743938],"domain_scores_gemma":[0.9991661,0.0004706081,0.0001021886,0.0001951783,0.00001717679,0.00004876433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008795574,0.000002275929,0.0009858499,0.0000053671,0.00000768787,0.000009447699,0.0003263553,0.04041917,0.00002028614,0.00003944188,0.0008179497,0.9572782],"study_design_scores_gemma":[0.0001248815,0.00001984206,0.000475564,0.000007399404,0.000006664158,0.00007523129,0.0008002375,0.6919677,0.000004916845,0.001307522,0.3051446,0.00006543326],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7888147,0.001875561,0.03189832,0.02185139,0.002487075,0.002057143,0.0002268219,0.0004143502,0.1503746],"genre_scores_gemma":[0.9955446,0.0001501909,0.003311453,0.0002525718,0.0001092308,5.020453e-10,0.0001580858,0.000003271836,0.000470588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9572128,"threshold_uncertainty_score":0.9991593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0199258093657768,"score_gpt":0.2242891190863147,"score_spread":0.2043633097205379,"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."}}