{"id":"W3174532363","doi":"10.1609/aaai.v35i13.17371","title":"Amnesiac Machine Learning","year":2021,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":173,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Inference; General Data Protection Regulation; Computer security; Artificial intelligence; European union; Inversion (geology); Training set; Machine learning; Data Protection Act 1998; Business","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":[0.003107304,0.0008036179,0.0007078902,0.0006767865,0.0004797182,0.001299197,0.001562513,0.001113159,0.003620275],"category_scores_gemma":[0.02223438,0.0003143076,0.0006023521,0.0003905363,0.002893287,0.003173604,0.00286815,0.002664753,0.0009974365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000953133,"about_ca_system_score_gemma":0.00106328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001204164,"about_ca_topic_score_gemma":0.001005867,"domain_scores_codex":[0.9973742,0.0008215109,0.0001837698,0.0005531292,0.000844094,0.0002233489],"domain_scores_gemma":[0.987495,0.004781392,0.001402159,0.005362487,0.0007236185,0.0002354105],"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":[0.0005673328,0.0003182595,0.008999926,0.0004349921,0.0004063347,0.0007562779,0.0005821442,0.2313297,0.01814754,0.2523772,0.0235805,0.4624997],"study_design_scores_gemma":[0.00004293464,0.0002167489,0.002436402,0.0001105104,0.00007977214,0.001019041,0.0001055136,0.7115682,0.01814793,0.2512094,0.01500666,0.00005696797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0889845,0.001319328,0.8853726,0.004230671,0.0002035993,0.0001500527,0.000355551,0.003363818,0.01601988],"genre_scores_gemma":[0.9150393,0.0006952391,0.074195,0.0008232946,0.0001298302,0.0001267231,0.0003167846,0.0001651041,0.00850872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003620275,"threshold_uncertainty_score":0.01643324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070843089853789,"score_gpt":0.2383034027856965,"score_spread":0.2275949718871586,"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."}}