{"id":"W1753276653","doi":"10.4271/2004-01-0752","title":"Neural Network Based Data Fusion for Vehicle Positioning in Land Navigation System","year":2004,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"University of Calgary","keywords":"Sensor fusion; Computer science; Artificial neural network; Global Positioning System; Fusion; Computer vision; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005393773,0.0004372573,0.0005107744,0.0001142438,0.0003056968,0.00009363496,0.0006166706,0.0005432014,0.00002209289],"category_scores_gemma":[0.0001401839,0.000416327,0.0001590086,0.0006660991,0.0001556308,0.0005467849,0.0001426798,0.0006914549,0.00002411444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004990203,"about_ca_system_score_gemma":0.00003742805,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001010426,"about_ca_topic_score_gemma":0.02446889,"domain_scores_codex":[0.9972925,0.00007117992,0.0007925865,0.0006926151,0.0004554707,0.0006956353],"domain_scores_gemma":[0.9984609,0.0002510183,0.0000998373,0.0009530753,0.00006605036,0.0001691193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000287986,0.00008679929,0.0002666034,0.0001675514,0.00001289861,0.00003469388,0.00001335876,0.06754248,0.9263826,0.003152945,0.0004009555,0.001651101],"study_design_scores_gemma":[0.002258043,0.000670714,0.9903045,0.001225841,0.00007324744,0.00006199095,0.00004411809,0.0003890435,0.0006778576,0.000922296,0.002641913,0.0007303796],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896364,0.0002923418,0.00005271857,0.001184363,0.0004652703,0.001378463,0.000167244,0.00304954,0.003773614],"genre_scores_gemma":[0.9938521,0.00002343785,0.0041451,0.0003033941,0.0003478297,0.0001959768,0.001015677,0.0001059331,0.00001051344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.990038,"threshold_uncertainty_score":0.9998289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131095105639892,"score_gpt":0.2386743528880055,"score_spread":0.2255648423240163,"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."}}