{"id":"W4412611010","doi":"10.1109/jiot.2025.3592155","title":"Joint Computational Resource Allocation and Layer Partitioning for Federated Learning","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Western University","funders":"","keywords":"Computer science; Resource allocation; Joint (building); Resource management (computing); Distributed computing; Layer (electronics); Computer network; Resource (disambiguation)","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":[0.001633814,0.000831317,0.0009370932,0.0004055256,0.0006427593,0.0008912583,0.001850823,0.0007522965,0.001297341],"category_scores_gemma":[0.003477163,0.0002844184,0.0004726861,0.0005253957,0.0007656537,0.001894706,0.001803404,0.001205744,0.0002501646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000767,"about_ca_system_score_gemma":0.001569477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004126627,"about_ca_topic_score_gemma":0.004377269,"domain_scores_codex":[0.9991003,0.000278137,0.00005077714,0.0002260961,0.0001581799,0.0001866152],"domain_scores_gemma":[0.9989265,0.0004143859,0.0001073381,0.0002818721,0.0001749836,0.00009507472],"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":[0.00024093,0.0001704217,0.001115492,0.00006537335,0.0000446292,0.00009555617,0.000090441,0.8716236,0.003382497,0.01155464,0.002005682,0.1096107],"study_design_scores_gemma":[0.000005833753,0.00001787839,0.00005719644,0.000002493347,0.00000326206,0.000009728009,0.000007762283,0.9952348,0.0006967415,0.003782982,0.0001777005,0.000003499823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0297195,0.0002093733,0.9678005,0.0001708788,0.00004456841,0.00005196868,0.00003502935,0.0007334398,0.001234691],"genre_scores_gemma":[0.8889548,0.00009157458,0.109519,0.000139849,0.00002548392,0.00009014599,0.00009431754,0.00005040862,0.001034542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004126627,"threshold_uncertainty_score":0.008640528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03421152351164703,"score_gpt":0.2890245423989307,"score_spread":0.2548130188872837,"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."}}