{"id":"W1198948360","doi":"10.1007/s10291-015-0484-y","title":"Modeling and verifying the impact of time delay on INS-aided GNSS PLLs","year":2015,"lang":"en","type":"article","venue":"GPS Solutions","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"GNSS applications; Inertial navigation system; Satellite system; Computer science; Phase-locked loop; Bandwidth (computing); Acceleration; Navigation system; Real-time computing; Global Positioning System; Engineering; Simulation; Electronic engineering; Inertial frame of reference; Jitter; 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":[0.000649084,0.0006183279,0.000413079,0.0003179365,0.0003697516,0.0008583815,0.0007037356,0.0006820575,0.002370839],"category_scores_gemma":[0.004511544,0.0003988835,0.000360423,0.0002606873,0.0004929437,0.0009589174,0.000564795,0.0005581668,0.0003895526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007917291,"about_ca_system_score_gemma":0.001311426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01358266,"about_ca_topic_score_gemma":0.009195749,"domain_scores_codex":[0.999442,0.0001010331,0.00003097999,0.00009021872,0.0002414802,0.00009415617],"domain_scores_gemma":[0.9984805,0.0007878903,0.0001854266,0.0002222884,0.0002977774,0.00002610755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001046982,0.00002182605,0.001219439,0.00004458381,0.00001139944,0.00007515254,0.00003953668,0.9819669,0.007110538,0.002617661,0.0001306312,0.006657659],"study_design_scores_gemma":[0.000009415598,0.00002748957,0.0002086942,0.000003629106,0.000006316369,0.00001259586,0.000007593954,0.9933848,0.005619007,0.0004690667,0.0002486342,0.000002731061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3739029,0.0002040697,0.6143646,0.0002047056,0.0001335026,0.00006049521,0.0003101081,0.001802597,0.009016964],"genre_scores_gemma":[0.9878369,0.00004632958,0.01088636,0.00001304115,0.00000582495,0.00001252098,0.00005514428,0.00005037213,0.001093623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01358266,"threshold_uncertainty_score":0.02700716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04543749683613862,"score_gpt":0.2666128381947012,"score_spread":0.2211753413585625,"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."}}