{"id":"W2563658259","doi":"10.1109/itsc.2016.7795533","title":"Cooperative localization via DSRC and multi-sensor multi-target track association","year":2016,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Dedicated short-range communications; Ranging; Transceiver; Global Positioning System; Computer science; Real-time computing; Kalman filter; Host (biology); Process (computing); Track (disk drive); Embedded system; Wireless; Telecommunications; 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":[0.0001637751,0.0001622562,0.0001666651,0.00004362675,0.00006000532,0.00003612727,0.0000521062,0.0001589255,0.0001840511],"category_scores_gemma":[0.00008840799,0.0001200051,0.00003079997,0.000113292,0.00001916331,0.0002386352,0.00001624789,0.00008572511,0.0001703071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002061682,"about_ca_system_score_gemma":0.00000778651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001343437,"about_ca_topic_score_gemma":0.0001443814,"domain_scores_codex":[0.9991354,0.00005329613,0.000201726,0.0001942112,0.0001381329,0.0002771806],"domain_scores_gemma":[0.9995551,0.00009031378,0.0000365005,0.0001233627,0.0001022473,0.00009249354],"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":[0.000007488033,0.00006995995,0.01626443,0.00002893494,0.0001509465,0.000007966053,0.0004664303,0.9283421,0.04063177,0.00007523412,0.004783691,0.00917103],"study_design_scores_gemma":[0.001082001,0.00001534127,0.004879361,0.00002128076,0.00001364705,0.000002850705,0.00002488802,0.9773036,0.01257741,0.00001014882,0.003858817,0.0002106184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05980574,0.0002044912,0.93863,0.0001331466,0.0002060165,0.0002643301,0.00001302206,0.000412111,0.0003310856],"genre_scores_gemma":[0.9795754,0.0001339387,0.01678552,0.0001143123,0.00009790489,0.00001769753,0.00001958644,0.00004851385,0.003207117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9218445,"threshold_uncertainty_score":0.4893666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009533555439368287,"score_gpt":0.2113376167074725,"score_spread":0.2018040612681042,"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."}}