{"id":"W4386275784","doi":"10.1109/jsac.2023.3310106","title":"Differentially Private Federated Multi-Task Learning Framework for Enhancing Human-to-Virtual Connectivity in Human Digital Twin","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Concordia University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Scheme (mathematics); Task (project management); Process (computing); Differential privacy; Distributed computing; Artificial intelligence; Human–computer interaction; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003104961,0.0005473178,0.001018462,0.0004484327,0.0009218148,0.001339298,0.001967915,0.001320824,0.001584569],"category_scores_gemma":[0.007485933,0.0002450244,0.0004558585,0.0006907755,0.001437074,0.003703141,0.00336384,0.001554934,0.0002636286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00110928,"about_ca_system_score_gemma":0.001754722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002375779,"about_ca_topic_score_gemma":0.002024945,"domain_scores_codex":[0.9980484,0.0007008354,0.00009416127,0.000444255,0.0004134074,0.0002988723],"domain_scores_gemma":[0.9970222,0.001282732,0.0002860789,0.000806134,0.0003630725,0.0002397516],"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":[0.0005180425,0.0002319047,0.002134508,0.00008492924,0.00005474691,0.0003464384,0.0003281349,0.7957491,0.005002422,0.07061353,0.001846098,0.1230901],"study_design_scores_gemma":[0.00001122434,0.00004255669,0.00008801409,0.000003082896,0.00000579044,0.00004128542,0.00001526908,0.9806799,0.0009120207,0.01780329,0.000391513,0.000006166808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03223396,0.0001237534,0.9658836,0.000242257,0.00002620164,0.00004306018,0.00004176812,0.000290079,0.001115279],"genre_scores_gemma":[0.9387389,0.00008219729,0.05936615,0.00009036747,0.00002161639,0.00006414255,0.00006613411,0.00002539917,0.001545099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003104961,"threshold_uncertainty_score":0.01642078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05470206361391927,"score_gpt":0.3433514664349823,"score_spread":0.2886494028210631,"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."}}