{"id":"W4402157326","doi":"10.1109/icc51166.2024.10622238","title":"Federated Unlearning with Multiple Client Partitions","year":2024,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science","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":[0.00251341,0.001198558,0.001651134,0.0007184624,0.001143384,0.00151705,0.002630863,0.001546973,0.001832439],"category_scores_gemma":[0.008719624,0.0005944009,0.000844172,0.0009400311,0.001195757,0.004910019,0.003228572,0.002391172,0.0006429211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639499,"about_ca_system_score_gemma":0.002141124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00476537,"about_ca_topic_score_gemma":0.005403598,"domain_scores_codex":[0.9982357,0.0005503884,0.000116707,0.0004747845,0.0003706545,0.0002516471],"domain_scores_gemma":[0.9956679,0.001554197,0.0002440423,0.001616575,0.000694883,0.000222386],"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":[0.0008061624,0.0004699094,0.004273436,0.00006892718,0.00007831558,0.0002063528,0.0002580116,0.6353565,0.00527226,0.008471103,0.003461387,0.3412775],"study_design_scores_gemma":[0.00001450242,0.00003167783,0.00007855127,0.000002735234,0.000004698764,0.00002686251,0.00002137041,0.9929208,0.0022018,0.004465314,0.0002268498,0.00000482047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09346133,0.0002837246,0.8987831,0.0003539271,0.00005314804,0.0001677128,0.0001051157,0.005285391,0.001506557],"genre_scores_gemma":[0.7980523,0.00007879245,0.198636,0.0003022259,0.00002735864,0.0001891613,0.0004023951,0.0001845017,0.002127238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00476537,"threshold_uncertainty_score":0.01329231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167005082175975,"score_gpt":0.2324092969783063,"score_spread":0.2207392461565466,"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."}}