{"id":"W6912806176","doi":"10.5281/zenodo.6583266","title":"Learning to Generate Inversion-Resistant Model Explanations","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Inversion (geology); Rendering (computer graphics); Artificial neural network; Adversary; Deep neural networks; Threat model; Minimax; Adversarial system","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":[0.00199282,0.00102601,0.000630628,0.0005141069,0.0003225912,0.0009410846,0.001191273,0.001609518,0.002134763],"category_scores_gemma":[0.01280816,0.0004408197,0.0009410004,0.0002342479,0.001871194,0.002032976,0.002728081,0.00287804,0.0003749952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009170495,"about_ca_system_score_gemma":0.0009018132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006337059,"about_ca_topic_score_gemma":0.0008036987,"domain_scores_codex":[0.9985952,0.0005507242,0.0000524313,0.000286404,0.0003596628,0.000155666],"domain_scores_gemma":[0.9946021,0.0035183,0.000550026,0.001020289,0.00020143,0.0001078132],"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":[0.0005198967,0.0001274016,0.003781458,0.0001906314,0.000169733,0.0005490361,0.0004097075,0.7449028,0.02383666,0.1384577,0.003306391,0.0837485],"study_design_scores_gemma":[0.00002091152,0.00007026993,0.0001691417,0.00002009101,0.0000167806,0.0001002683,0.00002266255,0.9436072,0.006683733,0.04845751,0.0008183284,0.00001320524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08829303,0.0002666782,0.9058511,0.001136062,0.00006715554,0.000099254,0.000169455,0.001389684,0.002727584],"genre_scores_gemma":[0.9430621,0.0001482509,0.05442842,0.0003612145,0.00003195451,0.00009040969,0.0002000241,0.0001103719,0.00156728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002134763,"threshold_uncertainty_score":0.01053917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03594158688028365,"score_gpt":0.2502878349863321,"score_spread":0.2143462481060484,"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."}}