{"id":"W2491532368","doi":"10.1007/s10291-016-0556-7","title":"Study on the cross-correlation of GNSS signals and typical approximations","year":2016,"lang":"en","type":"article","venue":"GPS Solutions","topic":"GNSS positioning and interference","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Montreal Police Service","funders":"","keywords":"GNSS applications; GPS signals; Global Positioning System; Doppler effect; Galileo (satellite navigation); Cross-correlation; Satellite; Frequency domain; SIGNAL (programming language); Computer science; Correlation; Satellite navigation; Remote sensing; Algorithm; Mathematics; Assisted GPS; Physics; Telecommunications; Statistics; Geography","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":[0.002982231,0.0008516865,0.0005328496,0.001129839,0.0005352777,0.001200606,0.001020908,0.0009398538,0.001732814],"category_scores_gemma":[0.01799584,0.0004301034,0.000851751,0.001448537,0.001385897,0.001935187,0.000901888,0.001692356,0.0003392466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006418619,"about_ca_system_score_gemma":0.0006269137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002372599,"about_ca_topic_score_gemma":0.001222892,"domain_scores_codex":[0.9988133,0.0004754716,0.00004015285,0.000185253,0.000376244,0.0001096839],"domain_scores_gemma":[0.9896679,0.008113986,0.0004793563,0.0005721711,0.001033642,0.000133058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000111465,0.00005091138,0.004331904,0.0003072892,0.0001456248,0.0007231964,0.0003173187,0.4722931,0.005507269,0.4971486,0.0019658,0.0170975],"study_design_scores_gemma":[0.000004203097,0.00002567118,0.001320803,0.00004523317,0.00003628696,0.0004419746,0.00005243988,0.9627564,0.001744688,0.03199629,0.001552882,0.00002315039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0887649,0.003078706,0.8924367,0.0004901324,0.0001449361,0.00002103867,0.0001121126,0.000214369,0.01473699],"genre_scores_gemma":[0.9239559,0.004420133,0.06282288,0.0002274166,0.000458143,0.00005655785,0.0003529425,0.0002914316,0.007414549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002982231,"threshold_uncertainty_score":0.01577175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04311700835060359,"score_gpt":0.2697271622594955,"score_spread":0.2266101539088919,"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."}}