{"id":"W6929373501","doi":"10.48336/2w0n-xe71","title":"Blind-time domain motion compensation of and significant-wave height extraction from high-frequency (HF) radar data acquired on a floating platform","year":2023,"lang":"en","type":"article","venue":"Memorial University Research Repository (Memorial University)","topic":"Mobile and Web Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Radar; Autocorrelation; Antenna (radio); Continuous-wave radar; Doppler effect; Transmitter; Pulse-Doppler radar; Radar engineering details; Doppler radar","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001158831,0.0002230148,0.0003515231,0.001138964,0.001280745,0.0001762195,0.001766714,0.0002588726,0.00002581298],"category_scores_gemma":[0.0001220021,0.0002687632,0.00008592771,0.002457312,0.000320312,0.00203263,0.001308943,0.0003804996,0.00007447778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005076526,"about_ca_system_score_gemma":0.0004271789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002681296,"about_ca_topic_score_gemma":0.00009770398,"domain_scores_codex":[0.9963813,0.0007061174,0.0003059097,0.00107421,0.001061975,0.0004704217],"domain_scores_gemma":[0.9966119,0.0009477744,0.0002850815,0.001458077,0.0004333293,0.0002638637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002751146,0.0005477112,0.0004519781,0.00007424058,0.0003186206,0.001517726,0.001998937,0.0003494446,0.8384056,0.1397285,0.00436936,0.009486723],"study_design_scores_gemma":[0.06224104,0.005652725,0.03625809,0.001136998,0.001055915,0.0001373668,0.02349215,0.2069323,0.5040657,0.05279116,0.1004288,0.005807822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613591,0.000007081552,0.02660329,0.0004189739,0.001918743,0.001010989,0.0001720823,0.0003365165,0.008173184],"genre_scores_gemma":[0.9890019,0.0000690583,0.006818572,0.000005211565,0.001687428,7.240281e-7,0.0004836176,0.00001928588,0.001914256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3343399,"threshold_uncertainty_score":0.9999765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07322582146880924,"score_gpt":0.2773840895649556,"score_spread":0.2041582680961463,"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."}}