{"id":"W4400188039","doi":"10.1109/mwc.018.2300534","title":"A Two-Dimensional Hybrid Federated Learning Framework for Secure Data Cooperation of Multiple Network Service Providers","year":2024,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Waterloo","funders":"Higher Education Discipline Innovation Project; Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Computer science; Service provider; Computer network; Computer security; Service (business); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004519726,0.0006098298,0.0009338288,0.0008068259,0.001133247,0.001673992,0.002755449,0.001615071,0.001411087],"category_scores_gemma":[0.004214475,0.0002762801,0.000788003,0.001158562,0.001094193,0.003327045,0.004069015,0.001298654,0.0003902086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330576,"about_ca_system_score_gemma":0.002483041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004345801,"about_ca_topic_score_gemma":0.004573273,"domain_scores_codex":[0.9977531,0.0008446837,0.0001120098,0.0004876034,0.0004558087,0.0003468572],"domain_scores_gemma":[0.9983314,0.0005198704,0.0001453134,0.000451804,0.0003665243,0.0001851228],"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":[0.0003252263,0.0003061361,0.002152407,0.0001001582,0.0001147837,0.0002864207,0.0002995011,0.7428942,0.003550746,0.05517145,0.004335486,0.1904634],"study_design_scores_gemma":[0.0000081572,0.00003584345,0.00007783889,0.000004736335,0.0000067316,0.00004290071,0.00003194724,0.9830661,0.0006364313,0.01523089,0.0008518703,0.000006560641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01183002,0.0002142041,0.9860212,0.000290709,0.00002639669,0.00005298821,0.00004661437,0.0004591868,0.001058636],"genre_scores_gemma":[0.6782185,0.0001982675,0.317939,0.0002773552,0.0000443,0.0001563491,0.0002309905,0.00004748017,0.002887735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004519726,"threshold_uncertainty_score":0.02390289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07267240013407894,"score_gpt":0.3320478669802058,"score_spread":0.2593754668461269,"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."}}