{"id":"W4382561979","doi":"10.1109/tnsm.2023.3282130","title":"Guest Editorial: Special Section on the Latest Developments in Federated Learning for the Management of Networked Systems and Resources","year":2023,"lang":"en","type":"editorial","venue":"IEEE Transactions on Network and Service Management","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Computer science; Special section; Context (archaeology); Learning Management; Data science; Section (typography); Service (business); Knowledge management; 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":[0.001745538,0.0003966317,0.0003802593,0.0002209761,0.0009221045,0.0005527458,0.004513307,0.0004182948,0.000001162557],"category_scores_gemma":[0.00007760506,0.0002876796,0.0000564153,0.001255391,0.00006405135,0.0001441682,0.001089129,0.0009958474,0.000005732985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001483241,"about_ca_system_score_gemma":0.00002579825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001993482,"about_ca_topic_score_gemma":0.0005559183,"domain_scores_codex":[0.9971488,0.0002074451,0.0005522037,0.0007952579,0.000785346,0.0005109925],"domain_scores_gemma":[0.9956244,0.002185288,0.0003042067,0.001717366,0.0001259168,0.00004287772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001196665,0.00004223164,0.000001530477,0.0004704879,0.0004257536,0.000007514639,0.0001101829,0.08812734,1.476292e-7,0.0001030001,0.9035448,0.007047393],"study_design_scores_gemma":[0.0007101322,0.0001350523,0.000051633,0.001209413,0.0001288644,4.14044e-7,0.0004059716,0.08258221,0.000002242806,0.0004339536,0.9140461,0.0002940292],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00006345796,0.000114481,0.05057667,0.00277714,0.9439633,0.001641675,0.00002219564,0.000323261,0.0005177775],"genre_scores_gemma":[0.002295691,0.01062323,0.002154445,0.00008955913,0.9827825,0.001246909,0.00006208415,0.00009251272,0.0006530242],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.04842222,"threshold_uncertainty_score":0.9999576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021955424056407,"score_gpt":0.2444029818308377,"score_spread":0.2241834275902736,"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."}}