{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003338512,0.000574194,0.0003246134,0.001120989,0.0006595926,0.001373744,0.00158025,0.0007051374,0.007015442],"category_scores_gemma":[0.00117574,0.000179865,0.000351461,0.001418384,0.0004253093,0.001057938,0.001515634,0.000695462,0.002341769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271361,"about_ca_system_score_gemma":0.001817191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005839255,"about_ca_topic_score_gemma":0.005751615,"domain_scores_codex":[0.9994577,0.00007865432,0.00002272276,0.00007468591,0.0002688753,0.00009738055],"domain_scores_gemma":[0.9996544,0.00003415382,0.00003406885,0.00007578889,0.000142071,0.0000595547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000287376,0.0001145878,0.002453591,0.0006906891,0.00008626148,0.0004090264,0.0001974801,0.1282872,0.01675689,0.2583556,0.1478183,0.4445429],"study_design_scores_gemma":[0.0001212568,0.0003728671,0.001776225,0.0001534514,0.00008484186,0.0007686344,0.0002084694,0.4405226,0.01534213,0.05027062,0.4902981,0.00008076504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02458169,0.002700456,0.8413218,0.001372444,0.001006661,0.001062725,0.002328127,0.02066594,0.1049602],"genre_scores_gemma":[0.6663746,0.002435226,0.2880874,0.0003882943,0.0002578824,0.0009614988,0.008741594,0.0006451758,0.03210828],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007015442,"threshold_uncertainty_score":0.02346897,"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."}}