{"id":"W4206569943","doi":"10.22215/etd/2021-14772","title":"Enhanced Design, Optimal Tuning, and Parallel Real-Time Implementation of Monocular Visual-Inertial-GNSS Navigation System","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"GNSS applications; Computer science; Robustness (evolution); Kalman filter; Sensor fusion; Real-time computing; Inertial navigation system; Artificial intelligence; Global Positioning System; Control engineering; Inertial frame of reference; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001618159,0.0003122124,0.0004544663,0.0001539537,0.00006381005,0.00006925108,0.00006986907,0.0002767596,0.00008992251],"category_scores_gemma":[0.00000833453,0.0003416412,0.00008146477,0.0002057862,0.00001129882,0.0001278436,0.000009259375,0.0001111718,0.000007559086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001111491,"about_ca_system_score_gemma":0.00006323851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002773404,"about_ca_topic_score_gemma":0.00003570205,"domain_scores_codex":[0.9984494,0.00008262495,0.0006648799,0.0003067557,0.0002833645,0.0002129666],"domain_scores_gemma":[0.9992443,0.0000440893,0.0002035061,0.0001820291,0.000251609,0.00007452348],"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":[0.00003346763,0.0000152464,0.000012658,0.001279353,0.0001493285,0.000009076961,0.0008687352,0.5084052,0.4863063,0.0003906089,0.0001110405,0.002419017],"study_design_scores_gemma":[0.0004154033,0.0000721953,0.0002527799,0.0003666913,0.0001253179,0.000002861611,0.003009858,0.6701912,0.3252547,0.000004783129,0.000005985786,0.0002982194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5044186,0.0002326551,0.4933969,0.000002694913,0.000231637,0.0005192521,0.000009503077,0.0002072586,0.0009815091],"genre_scores_gemma":[0.9691709,0.0003325292,0.0224003,0.000002717461,0.00007455374,0.00006527767,0.007137767,0.0001144192,0.0007015328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4709966,"threshold_uncertainty_score":0.9999036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00796396182259911,"score_gpt":0.2605186572738662,"score_spread":0.2525546954512671,"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."}}