{"id":"W2105449745","doi":"10.1109/taes.2007.357123","title":"ASPeCT: Unambiguous sine-BOC(n,n) acquisition/tracking technique for navigation applications","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"GNSS positioning and interference","field":"Engineering","cited_by":214,"is_retracted":false,"has_abstract":true,"ca_institutions":"3v Geomatics (Canada); University of Calgary","funders":"","keywords":"GNSS applications; Sine; Galileo (satellite navigation); Satellite navigation; Ranging; Computer science; Tracking (education); Satellite system; Binary offset carrier modulation; GNSS augmentation; Global Positioning System; Electronic engineering; Real-time computing; Engineering; Remote sensing; Telecommunications; Mathematics; Bandwidth (computing); Geography; Frequency modulation","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":[0.0002747134,0.000189701,0.0001741884,0.0001301677,0.0002938483,0.00009459836,0.00008675705,0.0001516693,0.000005261602],"category_scores_gemma":[0.000001012532,0.0002068957,0.00006891765,0.0002420139,0.00003432557,0.0001283769,4.348898e-7,0.0002835231,0.00001796964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002745123,"about_ca_system_score_gemma":0.00002623137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004514832,"about_ca_topic_score_gemma":0.00003425681,"domain_scores_codex":[0.9989161,0.00001419608,0.0002601666,0.0002438384,0.0001228663,0.0004427707],"domain_scores_gemma":[0.9995127,0.00007719156,0.00004509735,0.0002014195,0.00008320143,0.00008035347],"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":[0.0001472717,0.0003115512,0.00003260782,0.0008543506,0.0003294453,0.000003278839,0.0007862018,0.1110669,0.8305193,0.01523627,0.0007417216,0.03997111],"study_design_scores_gemma":[0.001031793,0.0007330726,0.0001552896,0.000578118,0.0001394432,0.0003212627,0.0005203668,0.02081108,0.9686331,0.001042352,0.005229401,0.0008047245],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01732157,0.0008590007,0.9791236,0.00004723886,0.0003027816,0.0009497638,0.00002517427,0.0003753712,0.0009955352],"genre_scores_gemma":[0.9980581,0.0001505763,0.0003074657,0.00002274201,0.0001245256,0.0009035292,0.00001679091,0.00004532077,0.000370956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9807366,"threshold_uncertainty_score":0.8436962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007509754484229409,"score_gpt":0.2344003688460766,"score_spread":0.2268906143618472,"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."}}