{"id":"W4385597971","doi":"10.1016/j.future.2023.07.035","title":"Edge aggregation placement for semi-decentralized federated learning in Industrial Internet of Things","year":2023,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Server; Edge computing; Edge device; Distributed computing; Enhanced Data Rates for GSM Evolution; Resource allocation; Block (permutation group theory); Computer network; Cloud computing; Artificial intelligence; Operating system","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":[0.001078549,0.0004098586,0.001100451,0.0004335153,0.001383415,0.001283463,0.001486365,0.001063259,0.002551864],"category_scores_gemma":[0.002090352,0.0002529494,0.000464656,0.0007820633,0.0005466481,0.001858058,0.001940543,0.0007100279,0.000424653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007859363,"about_ca_system_score_gemma":0.001140733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001955991,"about_ca_topic_score_gemma":0.003610901,"domain_scores_codex":[0.9992926,0.0001892822,0.00003925826,0.0001761886,0.0001315582,0.0001710608],"domain_scores_gemma":[0.9989458,0.0002968527,0.00008230953,0.0003524927,0.0002118223,0.0001107092],"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":[0.001043263,0.0004204784,0.002569679,0.0001161726,0.00007268426,0.0003545259,0.0002920553,0.6798426,0.009253064,0.03959014,0.008454542,0.2579909],"study_design_scores_gemma":[0.00001122466,0.00005752678,0.0002084413,0.000005032961,0.000007158009,0.00004428581,0.0000623179,0.9859284,0.001694573,0.01133722,0.0006378039,0.00000603569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1009129,0.0002179287,0.893984,0.0002805633,0.0001032376,0.00008423129,0.0001384434,0.001029922,0.003248828],"genre_scores_gemma":[0.9094222,0.00006331447,0.08767757,0.00006334842,0.00002504109,0.00003815943,0.0001297487,0.00003920693,0.002541516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002551864,"threshold_uncertainty_score":0.008536816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05546114425241865,"score_gpt":0.2733311077091663,"score_spread":0.2178699634567476,"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."}}