{"id":"W4249154197","doi":"10.1109/trustcom53373.2021.00049","title":"The Design and Implementation of Secure Distributed Image Classification Reasoning System for Heterogeneous Edge Computing","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Novelis (Canada)","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; Jiangsu Postdoctoral Research Foundation; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Edge computing; Software deployment; Distributed computing; Enhanced Data Rates for GSM Evolution; Artificial intelligence; Software 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":[0.0006614963,0.0004221252,0.0006697468,0.0007592928,0.001071453,0.001584546,0.001962404,0.0008767215,0.002088589],"category_scores_gemma":[0.001085481,0.0003010173,0.0005590503,0.0005885802,0.0004371479,0.002161607,0.001258219,0.0007531536,0.0007572785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009760923,"about_ca_system_score_gemma":0.001412994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004033175,"about_ca_topic_score_gemma":0.00207427,"domain_scores_codex":[0.999069,0.00010306,0.0001002417,0.0002713299,0.0003216127,0.0001348063],"domain_scores_gemma":[0.9994342,0.00005294687,0.00005332236,0.0001312652,0.0002641092,0.00006402931],"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":[0.00179909,0.0007656785,0.008482409,0.0004949347,0.0003020859,0.001559727,0.001081413,0.09193187,0.1854243,0.07070636,0.0258068,0.6116454],"study_design_scores_gemma":[0.0001583938,0.0002139596,0.001467895,0.00002850132,0.0001324944,0.0005630397,0.0001371614,0.9064549,0.06387753,0.009278152,0.0176048,0.00008318001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03020545,0.0002893719,0.9595469,0.0003803349,0.0001114895,0.0003068383,0.00007629699,0.004916148,0.004167312],"genre_scores_gemma":[0.7208944,0.0003414789,0.2707471,0.0004067135,0.00008959276,0.0003550238,0.000381962,0.0001333792,0.006650313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004033175,"threshold_uncertainty_score":0.008019388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06287388489026563,"score_gpt":0.34851535533868,"score_spread":0.2856414704484144,"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."}}