{"id":"W4389609686","doi":"10.1016/j.adhoc.2023.103380","title":"Verifying trust over IoT-ad hoc network-based applications under uncertainty","year":2023,"lang":"en","type":"article","venue":"Ad Hoc Networks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec","keywords":"Computer science; Wireless ad hoc network; Robustness (evolution); Internet of Things; Computer security; Trust management (information system); Component (thermodynamics); Business logic; Distributed computing; Risk analysis (engineering); Data science; Telecommunications; Wireless","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005892919,0.0003012921,0.0002945135,0.0001249723,0.0007127819,0.0003188625,0.001119136,0.0002133096,0.00001508622],"category_scores_gemma":[0.00001248618,0.0003065072,0.0001714077,0.002179507,0.00008252811,0.0001799143,0.0004898131,0.00048479,0.0002547223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351648,"about_ca_system_score_gemma":0.0001368619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009117934,"about_ca_topic_score_gemma":0.00001784745,"domain_scores_codex":[0.9973807,0.0001000143,0.0003851764,0.0007261931,0.000345055,0.001062914],"domain_scores_gemma":[0.9981214,0.0004318275,0.0001613749,0.0009950522,0.00008612034,0.0002041666],"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":[0.00001128547,0.00002636622,0.0005293092,0.00001263087,0.00002903707,0.00001252637,0.0001182984,0.7129357,0.000007437457,0.001702878,0.05805707,0.2265574],"study_design_scores_gemma":[0.0003550107,0.00003681904,0.003540787,0.0000483104,0.00001208396,0.000002505942,0.000008523506,0.7568821,0.000003016495,0.002323617,0.2364786,0.0003086384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01283045,0.003913016,0.971823,0.001044536,0.007330708,0.0004682347,7.048271e-7,0.001371641,0.001217733],"genre_scores_gemma":[0.8958815,0.001622638,0.06216784,0.01199627,0.02365098,0.0006121193,0.0002974806,0.000278413,0.003492786],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9096552,"threshold_uncertainty_score":0.9999387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02043041900081895,"score_gpt":0.260840256527225,"score_spread":0.240409837526406,"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."}}