{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002224316,0.0001051315,0.0001249676,0.00004900212,0.0001839686,0.0001312578,0.0004900008,0.00004426199,0.0003821795],"category_scores_gemma":[0.0002952727,0.00009889156,0.00005883542,0.0004537451,0.00002417547,0.0003701187,0.0005672575,0.000332634,0.0002239462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002511383,"about_ca_system_score_gemma":0.00006750315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003841296,"about_ca_topic_score_gemma":0.000007922465,"domain_scores_codex":[0.9988855,0.0001576212,0.0001400911,0.0003529064,0.0002279851,0.0002358902],"domain_scores_gemma":[0.9992784,0.0001237737,0.00004678704,0.0004007205,0.000078108,0.00007226886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000056171,0.00009981413,0.02827116,0.00003228612,0.0000526881,0.001027526,0.0010428,0.08283342,0.00318394,0.7410178,0.001447673,0.1409852],"study_design_scores_gemma":[0.0003160382,0.00002452828,0.001099838,0.00001012237,0.00000453773,0.0001521625,0.00005536649,0.9241019,0.003106981,0.002467767,0.06841158,0.0002491542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001092963,0.0001695165,0.9490972,0.001341069,0.0004232534,0.00002559985,1.082406e-7,0.0004793569,0.047371],"genre_scores_gemma":[0.6058581,0.00001568224,0.3767442,0.000736403,0.0001224173,0.000003031151,0.000005411479,0.00001398982,0.01650075],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8412685,"threshold_uncertainty_score":0.4184598,"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."}}