{"id":"W3011995057","doi":"10.1109/tdsc.2020.2980255","title":"LVBS: Lightweight Vehicular Blockchain for Secure Data Sharing in Disaster Rescue","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":236,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Higher Education Discipline Innovation Project; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Computer science; Data sharing; Computer security; Schedule; Tracing; Computer network","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004801333,0.0002605423,0.000329393,0.0001695573,0.0004638919,0.0001683452,0.0017165,0.000242084,0.000008960134],"category_scores_gemma":[0.00002086684,0.0002569425,0.00007238235,0.0006648531,0.00005613449,0.000226991,0.00009302877,0.0006288465,0.000008238378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003121976,"about_ca_system_score_gemma":0.00005274803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003963942,"about_ca_topic_score_gemma":0.0001807041,"domain_scores_codex":[0.9976445,0.00004893985,0.0004341369,0.001228829,0.0001882334,0.0004552992],"domain_scores_gemma":[0.9983985,0.0001701554,0.00008335707,0.001100892,0.00005867183,0.0001884353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004346958,0.002563902,0.001030346,0.001691993,0.0007935886,0.0004502829,0.04717293,0.261251,0.00892052,0.1775587,0.003795428,0.4943365],"study_design_scores_gemma":[0.0007582441,0.0001109694,0.00001820987,0.00007205249,0.00002037541,0.00002886775,0.0001810631,0.9883144,0.004286242,0.001969873,0.003934085,0.0003056265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1023473,0.0003168741,0.8909327,0.005360549,0.0001537709,0.0004985112,0.00004713512,0.0002928426,0.00005027069],"genre_scores_gemma":[0.9690458,0.00002986832,0.02989345,0.000858201,0.00008371556,0.00003709008,0.00001070704,0.0000237202,0.00001750236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8666984,"threshold_uncertainty_score":0.9999883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03712856388906087,"score_gpt":0.2653405133944984,"score_spread":0.2282119495054376,"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."}}