{"id":"W3103087864","doi":"10.3390/s20226567","title":"Optical and Mass Flow Sensors for Aiding Vehicle Navigation in GNSS Denied Environment","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Inertial navigation system; Odometry; Real-time computing; Air navigation; Computer science; Kalman filter; Navigation system; Heading (navigation); GNSS augmentation; Extended Kalman filter; Satellite system; Simulation; Engineering; Artificial intelligence; Global Positioning System; Mobile robot; Inertial frame of reference; Telecommunications; Robot; Aerospace 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":[],"consensus_categories":[],"category_scores_codex":[0.0000708083,0.0001236864,0.000146069,0.0000377214,0.00004200447,0.00002872386,0.00003611301,0.00008571214,0.000007911984],"category_scores_gemma":[0.00003889701,0.0001363917,0.00003170318,0.00008624774,0.00002468466,0.00004906716,0.000009602268,0.00009858127,0.00001676109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005577276,"about_ca_system_score_gemma":0.000003578662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002277444,"about_ca_topic_score_gemma":0.000001011701,"domain_scores_codex":[0.9992712,0.00001902645,0.0002003524,0.000189982,0.0001131283,0.0002062968],"domain_scores_gemma":[0.9997155,0.00006987547,0.000016343,0.00008036507,0.000011038,0.0001068997],"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":[0.00001601518,0.000005621958,0.0007278602,0.00006760562,0.000009133518,0.000009569571,0.0004067426,0.967253,0.03030842,0.0002432956,0.00003108659,0.000921629],"study_design_scores_gemma":[0.0005211268,0.00003985457,0.0005530741,0.00002013955,0.00001196311,0.000001743404,0.00018284,0.9748901,0.02306365,0.00009140091,0.0004671534,0.000156983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9518028,0.00005198138,0.04713188,0.0005052612,0.00006832005,0.000246782,0.000009142621,0.00008838847,0.00009537127],"genre_scores_gemma":[0.9881032,0.00004289421,0.01162264,0.00006280389,0.00007844656,0.000007715982,0.00003192541,0.00003687569,0.00001346542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03630035,"threshold_uncertainty_score":0.5561892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343364616968989,"score_gpt":0.1965664023825713,"score_spread":0.1831327562128814,"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."}}