{"id":"W4402835216","doi":"10.1109/vtc2024-spring62846.2024.10683298","title":"Real-Time UWB and IMU Fusion Positioning System for Urban Rail Transit with High Mobility","year":2024,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Inertial measurement unit; Computer science; Transit (satellite); Real-time computing; Sensor fusion; Fusion; Rail transit; Transport engineering; Public transport; Engineering; Artificial intelligence","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":[0.0005945282,0.0001018844,0.0001400335,0.00008303428,0.0002346674,0.0004495757,0.000523782,0.00005237596,0.00001469168],"category_scores_gemma":[0.000004677052,0.00007659104,0.00003325844,0.0003776596,0.00005819588,0.0004034523,0.0001827267,0.0001223777,0.00001701293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008742727,"about_ca_system_score_gemma":0.0000794115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001684997,"about_ca_topic_score_gemma":0.00002016767,"domain_scores_codex":[0.9988592,0.0001176331,0.0001722269,0.0003855322,0.0002423524,0.0002230423],"domain_scores_gemma":[0.9986693,0.0004062384,0.00002099879,0.0006913445,0.0001180523,0.00009403014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001779613,0.0001633788,0.0002366058,0.00130985,0.0001396331,0.00003697331,0.003251119,0.003095718,0.03827544,0.8946294,0.006796961,0.05188702],"study_design_scores_gemma":[0.0003288281,0.0001760141,0.0009478431,0.000279229,0.000008452761,0.00003247183,0.00005632722,0.994606,0.002438244,0.0004305841,0.0005436717,0.0001523902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1014217,0.0003646585,0.8901165,0.002584045,0.00007416967,0.0006815091,0.000006299511,0.0007906147,0.003960578],"genre_scores_gemma":[0.9493605,0.00003757363,0.04949255,0.00001684782,0.00004210011,0.00009011987,0.00001076185,0.00001240599,0.0009371173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9915102,"threshold_uncertainty_score":0.4335269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117185875952012,"score_gpt":0.252286440277184,"score_spread":0.2405678526819828,"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."}}