{"id":"W1965061176","doi":"10.1109/pimrc.2011.6140066","title":"CVI: Connected Vehicle Infrastructure for ITS","year":2011,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cluster analysis; Computer science; Overhead (engineering); Resilience (materials science); Intelligent transportation system; Computer network; Wireless sensor network; Distributed computing; Aggregate (composite); Real-time computing; Engineering; Artificial intelligence; Transport engineering","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":[0.00008799831,0.00009268051,0.0001005696,0.00002932861,0.00006291516,0.00004441859,0.0006976677,0.00007050646,0.0003356316],"category_scores_gemma":[0.00002828904,0.00007690739,0.0000422245,0.0001982269,0.00001551985,0.0002940312,0.0001572479,0.00007441011,0.00007238257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001385735,"about_ca_system_score_gemma":0.00003169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006251382,"about_ca_topic_score_gemma":0.00001070044,"domain_scores_codex":[0.9992345,0.00001818723,0.0001311802,0.0002697141,0.00009274279,0.000253658],"domain_scores_gemma":[0.9992941,0.00006736502,0.0000424192,0.0004139156,0.00009888635,0.0000833302],"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":[0.0000169421,0.00004309369,0.0007596217,0.00001472463,0.0000266615,0.000006665045,0.0009776861,0.0001293076,0.002026293,0.8987088,0.03972963,0.05756064],"study_design_scores_gemma":[0.0014007,0.000378669,0.02490999,0.00001626212,0.00001151703,0.00002223223,0.00003901743,0.8228889,0.05287624,0.05221783,0.04468482,0.0005538606],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02101902,0.00005434053,0.9537796,0.0001637869,0.0004937255,0.0003855588,0.000001855871,0.0003890909,0.02371296],"genre_scores_gemma":[0.8885287,0.000002188977,0.109655,0.0007722967,0.00008391318,0.00004550676,0.000001443695,0.000008761299,0.0009021871],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8675097,"threshold_uncertainty_score":0.3674931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367135436239312,"score_gpt":0.2249256853718627,"score_spread":0.2012543310094695,"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."}}