{"id":"W4412929609","doi":"10.3390/computers14080317","title":"Ensuring Zero Trust in GDPR-Compliant Deep Federated Learning Architecture","year":2025,"lang":"en","type":"article","venue":"Computers","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research","keywords":"Architecture; Zero (linguistics); Computer science; Computer security; Business; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008871065,0.0005538373,0.0006461781,0.0007470128,0.001261756,0.003322081,0.002396009,0.002125767,0.001103336],"category_scores_gemma":[0.01854648,0.0005475758,0.0009920062,0.0004290874,0.003069059,0.004945658,0.00562531,0.002809754,0.0004453404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003001763,"about_ca_system_score_gemma":0.005225928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004415663,"about_ca_topic_score_gemma":0.004977579,"domain_scores_codex":[0.992955,0.002400679,0.0007083931,0.001237669,0.001872181,0.00082607],"domain_scores_gemma":[0.9877046,0.002915884,0.001201591,0.005020287,0.002636818,0.0005207823],"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":[0.0008626634,0.0004340434,0.01149566,0.0003609991,0.0002306858,0.001180113,0.001756668,0.5349567,0.02530993,0.2588594,0.003860366,0.1606928],"study_design_scores_gemma":[0.0000301553,0.0001020817,0.000422065,0.00003747111,0.00003402127,0.0001494121,0.0000880303,0.9223211,0.01126552,0.06313551,0.002381347,0.00003323187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.054665,0.00006045943,0.9405867,0.0005636502,0.00002939162,0.0001396412,0.00006014262,0.001870266,0.002024905],"genre_scores_gemma":[0.8451437,0.00005743406,0.1523827,0.0002786813,0.00001191327,0.0001471082,0.0001509849,0.00008861016,0.00173895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008871065,"threshold_uncertainty_score":0.04691523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01826892856997713,"score_gpt":0.2559600051391999,"score_spread":0.2376910765692227,"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."}}