{"id":"W2135247072","doi":"10.1186/s40493-014-0010-0","title":"A trust-based framework for vehicular travel with non-binary reports and its validation via an extensive simulation testbed","year":2014,"lang":"en","type":"article","venue":"Journal of Trust Management","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education, India","keywords":"Testbed; Computer science; Intelligent transportation system; Path (computing); Trustworthiness; Binary decision diagram; Vehicular ad hoc network; Data mining; Wireless ad hoc network; Algorithm; Computer network; Transport engineering; Computer security; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004343739,0.0005912954,0.0006382004,0.0007008374,0.0007959225,0.001260031,0.001848598,0.001245617,0.00117737],"category_scores_gemma":[0.01301463,0.0002712617,0.0004181668,0.0004687233,0.001307528,0.001584152,0.001354445,0.001142817,0.0001382199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002237974,"about_ca_system_score_gemma":0.001909484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01518833,"about_ca_topic_score_gemma":0.007843927,"domain_scores_codex":[0.9975907,0.001490045,0.0001223384,0.0001929508,0.0004248125,0.0001791515],"domain_scores_gemma":[0.9931484,0.004528708,0.0005230417,0.0006618589,0.0008607076,0.0002773137],"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":[0.0001529638,0.0001723616,0.001684828,0.00004774101,0.00002668809,0.0001025941,0.0001750646,0.971064,0.001481715,0.01664097,0.0003627481,0.008088388],"study_design_scores_gemma":[0.00001798044,0.00005251266,0.0001248302,0.000003166466,0.000004716958,0.00001045903,0.00003343276,0.9974596,0.0005318315,0.001516857,0.0002402388,0.00000446789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4070353,0.0002201845,0.584502,0.0007394372,0.00007119396,0.0006629428,0.0002417024,0.0009386667,0.005588559],"genre_scores_gemma":[0.9228724,0.0000681826,0.07628176,0.00002320051,0.000006037824,0.0001685818,0.00008280513,0.00002168196,0.0004753954],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01518833,"threshold_uncertainty_score":0.03019989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008548800005193381,"score_gpt":0.2331116036565539,"score_spread":0.2245628036513605,"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."}}