{"id":"W1788170167","doi":"10.1109/aps.2005.1552109","title":"Extracting Wind Parameters from High Frequency Ground Wave Radar Backscatter","year":2005,"lang":"en","type":"article","venue":"","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Radar; Remote sensing; Backscatter (email); Doppler radar; Doppler effect; Wave radar; Position (finance); Geology; Extraction (chemistry); Radar cross-section; Computer science; Meteorology; Pulse-Doppler radar; Radar imaging; Acoustics; Environmental science; Physics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003336819,0.0005971646,0.0004464124,0.00111251,0.0002120205,0.0004956045,0.0003111262,0.0004338082,0.001048995],"category_scores_gemma":[0.0009270633,0.0003124382,0.0003253452,0.0006239604,0.0001592026,0.0005873459,0.0002944646,0.0004359153,0.001096807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008198465,"about_ca_system_score_gemma":0.0003634476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005042778,"about_ca_topic_score_gemma":0.00139287,"domain_scores_codex":[0.9998888,0.00001770414,0.000009547871,0.00002551687,0.00004629343,0.00001217803],"domain_scores_gemma":[0.999782,0.00007617742,0.00002435167,0.00003232937,0.0000772685,0.000007957317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008467347,0.00007800731,0.005252038,0.0002647295,0.00006359223,0.0001176263,0.00007219108,0.02437085,0.2580438,0.004004648,0.001259893,0.7063881],"study_design_scores_gemma":[0.00007916786,0.0002662141,0.02311558,0.00007567561,0.000109287,0.0007073827,0.00009400411,0.7194183,0.2363537,0.008209443,0.01144994,0.000121226],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02619914,0.0002794881,0.9721139,0.00002942145,0.00003887978,0.00004354341,0.0002449893,0.0004461904,0.0006044788],"genre_scores_gemma":[0.1248672,0.0004805403,0.872584,0.00001827919,0.00002791793,0.00007497463,0.0006480672,0.00007020708,0.001228806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00111251,"threshold_uncertainty_score":0.003509223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01886798778056117,"score_gpt":0.1965827746418195,"score_spread":0.1777147868612584,"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."}}