{"id":"W2123272317","doi":"10.1109/isssta.2008.16","title":"New L5/E5a Acquisition Algorithms: Analysis and Comparison","year":2008,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Robustness (evolution); GNSS applications; Ranging; Algorithm; Satellite navigation; Monte Carlo method; False alarm; Real-time computing; Data mining; Global Positioning System; Artificial intelligence; Telecommunications; Mathematics","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":[0.004294622,0.0007034155,0.0005765266,0.003506601,0.0003967448,0.001161256,0.001121799,0.001089822,0.002622783],"category_scores_gemma":[0.008979554,0.0002804841,0.0006260307,0.001766147,0.000610067,0.001856557,0.0009225515,0.0006274541,0.0008717926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168109,"about_ca_system_score_gemma":0.0008663582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002273396,"about_ca_topic_score_gemma":0.001596896,"domain_scores_codex":[0.9982088,0.000473684,0.0001522684,0.0001876785,0.0008633858,0.0001141808],"domain_scores_gemma":[0.9944208,0.003272183,0.0004492885,0.000478684,0.001278734,0.000100247],"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":[0.001168408,0.0002069017,0.0120758,0.0003164666,0.0002732966,0.0001120192,0.0001694855,0.2330352,0.008436171,0.03921603,0.002433672,0.7025566],"study_design_scores_gemma":[0.00005679464,0.0003067298,0.00425691,0.00004134385,0.00006392552,0.0002662197,0.00005364762,0.9784734,0.008150958,0.004742896,0.003538169,0.00004899241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06851257,0.003749989,0.9198935,0.0002101975,0.0001297384,0.0001261196,0.0001488621,0.0006956704,0.006533484],"genre_scores_gemma":[0.4160461,0.0022264,0.5775612,0.0001445729,0.0001605362,0.0002096784,0.0005909213,0.000177376,0.002883161],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004294622,"threshold_uncertainty_score":0.02271241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01470047002319944,"score_gpt":0.2312796573808105,"score_spread":0.216579187357611,"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."}}