{"id":"W4417509397","doi":"10.1109/icsit65336.2025.11293913","title":"Rewriting Memory: an Efficient Framework for Machine Unlearning in Pretrained Deep Models","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Rewriting; Focus (optics); Subject (documents); Rest (music); Noisy data","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":[0.002249214,0.001309703,0.001200118,0.0007743125,0.0006213481,0.001836789,0.004414401,0.001280069,0.004380336],"category_scores_gemma":[0.01089133,0.0006853803,0.00106902,0.0007974583,0.001561476,0.004113903,0.003730308,0.003861727,0.001773629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126441,"about_ca_system_score_gemma":0.0019347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003718858,"about_ca_topic_score_gemma":0.007744328,"domain_scores_codex":[0.998396,0.0004810996,0.0001108838,0.0004025344,0.0004473638,0.0001621141],"domain_scores_gemma":[0.9959368,0.001303989,0.000261166,0.001994219,0.0003741017,0.0001296973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003231243,0.0002133654,0.001174394,0.0002446412,0.0001725628,0.0003266813,0.0003362508,0.2248963,0.01348875,0.06551082,0.0118151,0.681498],"study_design_scores_gemma":[0.00002450332,0.0000686763,0.00008384718,0.00002313813,0.00002386158,0.00008984438,0.0000289273,0.9282039,0.01319785,0.05343766,0.004799049,0.00001875433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006803823,0.00028989,0.9863643,0.000240062,0.00007394447,0.00005768866,0.00009648428,0.004878048,0.00119574],"genre_scores_gemma":[0.3638807,0.0005952575,0.6231102,0.0006450887,0.0001854548,0.0004114158,0.0008240536,0.001476307,0.008871438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004414401,"threshold_uncertainty_score":0.01465374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02896581428280361,"score_gpt":0.3184475885131965,"score_spread":0.2894817742303929,"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."}}