{"id":"W2137352707","doi":"10.1504/ijvics.2005.007589","title":"An HSGPS, inertial and map-matching integrated portable vehicular navigation system for uninterrupted real-time vehicular navigation","year":2005,"lang":"en","type":"article","venue":"International Journal of Vehicle Information and Communication Systems","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Global Positioning System; Map matching; Inertial measurement unit; Inertial navigation system; Computer science; Real-time computing; Navigation system; Dead reckoning; Matching (statistics); Inertial frame of reference; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007794457,0.0001745265,0.0002575351,0.0003402007,0.0001538084,0.0004333888,0.0004229815,0.0001704112,0.000004471817],"category_scores_gemma":[0.0000350341,0.000164203,0.00005907058,0.0001450592,0.00005762724,0.00266661,0.00004407946,0.0002252197,0.00001056783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000266265,"about_ca_system_score_gemma":0.00004256497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001129723,"about_ca_topic_score_gemma":0.000004213057,"domain_scores_codex":[0.9981906,0.00009334928,0.001113262,0.00008553413,0.0003762387,0.0001409968],"domain_scores_gemma":[0.9979013,0.0000741127,0.0005704831,0.0002431787,0.001124949,0.00008594488],"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":[0.0004116181,0.0001353901,0.001382838,0.0007402725,0.0007067139,0.000009953263,0.009808564,0.80419,0.05172643,0.04014373,0.001537083,0.0892074],"study_design_scores_gemma":[0.001363116,0.00009116864,0.0003193414,0.0006578136,0.00003767414,0.0002613204,0.005120689,0.9647439,0.006122808,0.0001337554,0.02092584,0.0002226478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9167889,0.0007109196,0.08063609,0.000435,0.000422142,0.0003751646,0.00005507119,0.0003276807,0.0002489746],"genre_scores_gemma":[0.9962494,0.0002686677,0.002623375,0.00003475684,0.0001222134,0.00002906876,0.0006371904,0.00001939728,0.00001589699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1605538,"threshold_uncertainty_score":0.6696002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006543751754640801,"score_gpt":0.2373265935152441,"score_spread":0.2307828417606033,"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."}}