{"id":"W6903036975","doi":"10.1016/j.comcom.2025.108275","title":"Dynamic Split Federated Learning for resource-constrained IoT systems","year":2025,"lang":"en","type":"article","venue":"Computer Communications","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Architecture; Metadata; Server; Process (computing); Federated learning; Internet of Things; Aggregate (composite); Resource (disambiguation); Task (project management)","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0005719943,0.0001919427,0.0002616754,0.0003040613,0.0009811029,0.0006385614,0.0385177,0.0001494366,0.000001361074],"category_scores_gemma":[0.002610883,0.00020735,0.00008547183,0.0008822654,0.0002304022,0.0001516506,0.07524438,0.0004911736,0.00002059057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001525286,"about_ca_system_score_gemma":0.0001405474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002542586,"about_ca_topic_score_gemma":0.00001448543,"domain_scores_codex":[0.998313,0.0002689702,0.0004380853,0.0004864587,0.0001331865,0.0003602672],"domain_scores_gemma":[0.984338,0.001227053,0.0001618149,0.01402018,0.000202447,0.00005052935],"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":[0.00001236767,0.0002906459,0.0004487805,0.0001875132,0.0002916634,0.000003981871,0.0002453642,0.004805802,0.000470529,0.3508764,0.2725802,0.3697867],"study_design_scores_gemma":[0.0003046472,0.00003410374,0.0002627142,0.0001286938,0.000009695958,0.000007595028,0.00003833874,0.8743546,0.00002463867,0.02069576,0.1039719,0.0001673093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008642598,0.001055647,0.9477679,0.04504526,0.0003343115,0.0005860007,0.00001366447,0.001855126,0.00247785],"genre_scores_gemma":[0.2477734,0.00003953268,0.7512056,0.0003052928,0.00001407011,0.000190434,0.0001010154,0.00001364996,0.0003570364],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8695488,"threshold_uncertainty_score":0.9666844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03732138526178992,"score_gpt":0.3051612359449662,"score_spread":0.2678398506831763,"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."}}