{"id":"W2007065460","doi":"10.1155/2008/356267","title":"A Reconfigurable GNSS Acquisition Scheme for Time-Frequency Applications","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"GNSS positioning and interference","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Computer science; Block (permutation group theory); Satellite system; sort; Interference (communication); Key (lock); Scheme (mathematics); Real-time computing; GNSS augmentation; Electronic engineering; Telecommunications; Global Positioning System; Engineering","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":[0.0001777475,0.0001572984,0.0001756233,0.0001672998,0.0003367776,0.00007824961,0.00017817,0.00005768319,0.00008509057],"category_scores_gemma":[0.00001719656,0.0001535568,0.00005766283,0.0002371517,0.0000492216,0.0009213886,0.000003759792,0.0003630219,0.00006084821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001381276,"about_ca_system_score_gemma":0.00004604948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.790913e-7,"about_ca_topic_score_gemma":3.266665e-7,"domain_scores_codex":[0.9989972,0.00002145235,0.0003663994,0.0001692938,0.0001633314,0.0002822855],"domain_scores_gemma":[0.9995216,0.00007470125,0.0001086299,0.00008161636,0.0001309837,0.00008245043],"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":[0.0003271091,0.0005420725,0.002804265,0.0009245205,0.00006597525,0.00008763649,0.001635545,0.2229466,0.2404879,0.002100395,0.00291719,0.5251608],"study_design_scores_gemma":[0.007792309,0.002352767,0.004007604,0.01021106,0.0000922682,0.006124337,0.0007400699,0.5697933,0.2028571,0.1029545,0.08911852,0.003956161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1020881,0.02098287,0.7642673,0.0002373095,0.0003894287,0.0006819858,0.0000234862,0.0004886332,0.1108409],"genre_scores_gemma":[0.9860455,0.0005256217,0.01275351,0.00009995123,0.0002836481,0.00009129542,0.000008949117,0.00003274366,0.0001587589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8839574,"threshold_uncertainty_score":0.6261863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01464591929387731,"score_gpt":0.2627829373159415,"score_spread":0.2481370180220642,"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."}}