{"id":"W3011855346","doi":"10.1109/jiot.2020.2981005","title":"A Reliable Trust Computing Mechanism Based on Multisource Feedback and Fog Computing in Social Sensor Cloud","year":2020,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Computer science; Cloud computing; Overhead (engineering); Edge computing; Wireless sensor network; Network layer; Computer network; Distributed computing; The Internet; Computer security; Application layer; Layer (electronics); World Wide Web","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":[0.001139867,0.0002794279,0.0004953892,0.0002353851,0.0002679719,0.0004115573,0.0009560561,0.0001373736,0.000003854494],"category_scores_gemma":[0.0001457868,0.0002762335,0.0001623312,0.0003668019,0.00006143864,0.0003462123,0.000365073,0.001068638,0.0000125653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001033847,"about_ca_system_score_gemma":0.00006965535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007295357,"about_ca_topic_score_gemma":3.788498e-7,"domain_scores_codex":[0.9975235,0.0001725198,0.000787259,0.0004703427,0.0004995634,0.0005467667],"domain_scores_gemma":[0.9986143,0.0002704454,0.0006191115,0.0001536526,0.0001341662,0.0002083455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001764254,0.001660494,0.03682545,0.001651337,0.0006111651,0.003015961,0.429584,0.07601061,0.06195816,0.01035821,0.09733461,0.2792257],"study_design_scores_gemma":[0.001474172,0.0003071568,0.000661985,0.00047829,0.000008881324,0.0001408228,0.0001561307,0.988927,0.006514284,0.0005312141,0.0005199313,0.0002801185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5332286,0.00002406283,0.4609585,0.001699847,0.003435938,0.00009359591,1.52538e-7,0.00007986418,0.0004793766],"genre_scores_gemma":[0.936946,0.000001640557,0.05787847,0.002529234,0.002584622,2.399594e-7,4.056002e-7,0.00002573815,0.00003364425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9129164,"threshold_uncertainty_score":0.999969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285597574863074,"score_gpt":0.2473368662887126,"score_spread":0.2244808905400818,"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."}}