{"id":"W3172131091","doi":"10.48550/arxiv.2102.10618","title":"Towards the Unification and Robustness of Perturbation and Gradient\\n Based Explanations","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Unification; Robustness (evolution); Leverage (statistics); Perturbation (astronomy); Algorithm; Mathematical optimization; Artificial intelligence; Mathematics","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":[0.01655448,0.001783047,0.001737834,0.002647992,0.001315213,0.00337474,0.003630434,0.004384503,0.002295381],"category_scores_gemma":[0.1252783,0.001179995,0.00147313,0.001303288,0.006408234,0.008182815,0.006651391,0.006659319,0.0005355781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00282763,"about_ca_system_score_gemma":0.002490977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003793602,"about_ca_topic_score_gemma":0.0032901,"domain_scores_codex":[0.991798,0.004477261,0.0003793196,0.001465055,0.001592176,0.0002881221],"domain_scores_gemma":[0.8862696,0.09435095,0.005737756,0.009409535,0.002973337,0.001258895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000626977,0.0001428032,0.007149218,0.0004213165,0.0003072152,0.0002133338,0.0007914077,0.6438345,0.003110643,0.2188179,0.002844699,0.1217401],"study_design_scores_gemma":[0.00002312621,0.00005942965,0.0005154322,0.00004533595,0.00001827564,0.00004479359,0.00004329247,0.9013588,0.001109154,0.09595261,0.0008083603,0.00002138486],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02978893,0.001071556,0.9642723,0.001695011,0.00008035923,0.0001222972,0.0001147538,0.0006840423,0.00217078],"genre_scores_gemma":[0.5637163,0.001096921,0.4292524,0.0008885755,0.000367635,0.0003119096,0.0005967738,0.0005383397,0.003231288],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01655448,"threshold_uncertainty_score":0.08754945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1078599139298955,"score_gpt":0.2016576829367786,"score_spread":0.09379776900688316,"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."}}