{"id":"W2103571421","doi":"10.1109/vetecf.2008.252","title":"Vehicular Collaborative Technique for Location Estimate Correction","year":2008,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Multipath propagation; Vehicular ad hoc network; Global Positioning System; Real-time computing; Computer network; Wireless ad hoc network; Telecommunications; Wireless","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":[0.00004175235,0.00007501139,0.00007555803,0.0000755813,0.00009339508,0.0000077451,0.00004918574,0.00009498765,0.00001349111],"category_scores_gemma":[0.0000608267,0.00007116974,0.00001753769,0.0003390835,0.00003118872,0.00008819532,0.000005501119,0.00004629831,0.00001645534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005346647,"about_ca_system_score_gemma":0.00001734578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004282805,"about_ca_topic_score_gemma":0.000006011121,"domain_scores_codex":[0.999661,0.000004127312,0.0001034433,0.00007953824,0.00005047639,0.0001013667],"domain_scores_gemma":[0.9996973,0.00002119442,0.00001341549,0.00009488741,0.0001596392,0.0000135734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002979337,0.00004660878,0.001225796,0.0001668106,0.0000614379,0.000006954984,0.0006367465,0.7999276,0.06837191,0.01244605,0.1085787,0.008501572],"study_design_scores_gemma":[0.000135632,0.00003593298,0.0001716551,0.000009942938,0.000004446365,0.00001351882,0.00009489022,0.2048774,0.7886295,0.0003709543,0.005542777,0.0001133589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003294161,0.00007449553,0.9912214,0.00003014862,0.0003114703,0.0004516775,0.000002865537,0.00140024,0.003213504],"genre_scores_gemma":[0.9814546,0.0000496916,0.01766688,0.00002032095,0.00002318592,0.0003555511,0.00002165739,0.00001833023,0.0003897519],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9781604,"threshold_uncertainty_score":0.2902218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008531506838926412,"score_gpt":0.2305438862059899,"score_spread":0.2220123793670635,"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."}}