{"id":"W2187686889","doi":"","title":"Integrating Vision Derived Bearing Measurements with Differential GPS and UWB Ranges for Vehicle-to-vehicle Relative Navigation.","year":2013,"lang":"en","type":"article","venue":"Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bearing (navigation); Differential GPS; Global Positioning System; Computer science; Range (aeronautics); Differential (mechanical device); Computer vision; Remote sensing; Artificial intelligence; Geodesy; Engineering; Geology; Telecommunications; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006120602,0.0002255349,0.0003439344,0.0001097664,0.0002118224,0.00002937875,0.001060682,0.0001867757,0.000004517568],"category_scores_gemma":[0.0005383338,0.0001320279,0.0001898553,0.0003579363,0.0004704458,0.0004556865,0.0005118917,0.0003654368,0.000001020982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008774738,"about_ca_system_score_gemma":0.00002157215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006998119,"about_ca_topic_score_gemma":0.000006722676,"domain_scores_codex":[0.998049,0.00002474222,0.0008341436,0.0002575527,0.0006531161,0.0001814154],"domain_scores_gemma":[0.9978764,0.000144638,0.0008421921,0.0002487973,0.0008425503,0.00004539943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001027351,0.00007106831,0.01211814,0.0002381914,0.0001233365,2.408565e-8,0.000309427,0.003509096,0.9707531,0.003567275,0.00005533909,0.009152321],"study_design_scores_gemma":[0.0007895374,0.0001362182,0.08451777,0.004111291,0.00008283593,0.000003649867,0.0001078243,0.01305793,0.8900642,0.006775883,0.0001724815,0.0001803406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945311,0.00009521979,0.001453281,0.001906931,0.0004160968,0.001056695,0.00001998774,0.00007900808,0.0004416814],"genre_scores_gemma":[0.9928787,0.00002741554,0.006921747,0.00001969825,0.00003031014,0.00005019919,0.00000504947,0.00002704081,0.00003984645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0806888,"threshold_uncertainty_score":0.5383943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389686851915426,"score_gpt":0.2397620564230697,"score_spread":0.2258651879039155,"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."}}