{"id":"W2037305373","doi":"10.1109/oceans.2012.6404836","title":"Simulation of HF radar cross sections for swell contaminated seas","year":2012,"lang":"en","type":"article","venue":"","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Swell; Radar cross-section; Wind wave; Bistatic radar; Wave radar; Geology; Radar; Azimuth; Electromagnetic spectrum; Remote sensing; Meteorology; Computer science; Physics; Radar imaging; Telecommunications; Optics; Oceanography","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":[],"consensus_categories":[],"category_scores_codex":[0.0001328122,0.0000494176,0.00007402662,0.00002909178,0.0001037587,0.0000150114,0.00002826284,0.00004107008,0.0002875836],"category_scores_gemma":[0.00003830381,0.00003651745,0.00004379217,0.00007657118,0.00003485055,0.0001586527,0.000002036995,0.0000289088,0.00002381025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001632788,"about_ca_system_score_gemma":0.000009307088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004342221,"about_ca_topic_score_gemma":0.0001672044,"domain_scores_codex":[0.9995729,0.0000152046,0.0001137155,0.00006598605,0.00006866832,0.0001635649],"domain_scores_gemma":[0.9995789,0.0001871368,0.00004176013,0.00006044502,0.00007003189,0.00006172422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009158756,0.00004636033,0.2042671,0.00006515113,0.00004099481,5.52646e-7,0.0005603182,0.7622938,0.0002834475,0.0001894783,0.0003299251,0.03183134],"study_design_scores_gemma":[0.0002641438,0.00006143103,0.2762307,0.00000548732,0.00001237682,0.000002381979,0.0001666396,0.7144349,0.002490251,0.0001149895,0.006136779,0.00007993426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823892,0.0001032131,0.006820193,0.00003033565,0.0004387902,0.0001415591,0.00003562585,0.00002413852,0.01001698],"genre_scores_gemma":[0.9956852,0.000001968674,0.002248751,0.00005773018,0.0001317956,2.377218e-9,0.000060776,0.000001862071,0.001811953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07196365,"threshold_uncertainty_score":0.3148839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0229688356633948,"score_gpt":0.2697384517534246,"score_spread":0.2467696160900298,"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."}}