{"id":"W2996680849","doi":"10.1109/jsen.2019.2958791","title":"Robust Positioning for Road Information Services in Challenging Environments","year":2019,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Qatar National Research Fund","keywords":"GNSS applications; Inertial measurement unit; Inertial navigation system; Computer science; Global Positioning System; Satellite system; Real-time computing; Hybrid positioning system; Positioning system; Inertial frame of reference; Simulation; Engineering; Artificial intelligence; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001412857,0.00009190887,0.0001000268,0.0001403862,0.00006807271,0.00006348767,0.00005849089,0.00006663625,0.00003213613],"category_scores_gemma":[0.000002565524,0.00009510165,0.00004485308,0.00006334876,0.000003781028,0.0007363057,0.000003293125,0.0001795869,0.00009513146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001116984,"about_ca_system_score_gemma":0.000002813908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009746771,"about_ca_topic_score_gemma":0.000003130353,"domain_scores_codex":[0.9993455,0.00001319638,0.0002572239,0.00005162831,0.0001320704,0.0002004224],"domain_scores_gemma":[0.9998121,0.00001545581,0.00005462447,0.00005830502,0.00001659415,0.00004292023],"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":[0.00001594243,0.000005220086,0.0004196239,0.00004962521,0.00001244306,0.000001667443,0.0008332257,0.9774312,0.0178465,0.00001516869,0.00002864564,0.003340763],"study_design_scores_gemma":[0.001301355,0.00005418395,0.01138889,0.0001999975,0.0000123879,0.00008999123,0.0006370925,0.9657325,0.01811104,0.00008319624,0.002144571,0.0002448121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927829,0.0000540109,0.004946624,0.00003973758,0.0007609325,0.0001584108,0.000003918431,0.00003348138,0.001219984],"genre_scores_gemma":[0.9991086,0.0000748227,0.0005186265,0.00003586584,0.0001896321,0.00000288393,0.00001454327,0.00001456511,0.00004046579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01169869,"threshold_uncertainty_score":0.3878133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007086050524640577,"score_gpt":0.1881666248621377,"score_spread":0.1810805743374971,"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."}}