{"id":"W4404689564","doi":"10.1109/oceans55160.2024.10753830","title":"Quantification of the Effects of Preprocessing Filters on the Performance of GNSS-R Based Sea Ice Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency","keywords":"GNSS applications; Preprocessor; Sea ice; Computer science; Remote sensing; Geology; Global Positioning System; Artificial intelligence; Telecommunications; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002001116,0.0009347657,0.0004987522,0.0008351671,0.0003314132,0.001007064,0.0003407329,0.0006630007,0.000647864],"category_scores_gemma":[0.01215139,0.0002258821,0.0004165854,0.0007177479,0.0003179953,0.0007362787,0.0003912199,0.000407256,0.0005096709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002871184,"about_ca_system_score_gemma":0.0004276559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002355764,"about_ca_topic_score_gemma":0.001869999,"domain_scores_codex":[0.9989979,0.0001798415,0.0001047728,0.0001799201,0.0003640852,0.0001735452],"domain_scores_gemma":[0.9934008,0.004696488,0.000424401,0.0003905477,0.00101363,0.00007417421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005520511,0.000585922,0.04855411,0.000585886,0.0003683988,0.0004159344,0.0003143969,0.06162141,0.5461618,0.0003984429,0.0009320533,0.3345411],"study_design_scores_gemma":[0.00006485231,0.003199286,0.1643201,0.00006297419,0.0003334834,0.000666135,0.0002600473,0.1987226,0.629909,0.0003487734,0.002013373,0.00009929365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.925119,0.0008547677,0.07108666,0.0001033376,0.000089771,0.00008306761,0.0003130726,0.0009087941,0.001441553],"genre_scores_gemma":[0.9368675,0.0004766611,0.06048677,0.00008155651,0.00004343073,0.00006491867,0.0009811654,0.0001226439,0.0008753096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002355764,"threshold_uncertainty_score":0.01058304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008870864440355097,"score_gpt":0.2003835626355745,"score_spread":0.1915126981952194,"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."}}