{"id":"W1965936844","doi":"10.1109/dsn.2014.2","title":"Quantifying the Accuracy of High-Level Fault Injection Techniques for Hardware Faults","year":2014,"lang":"en","type":"article","venue":"","topic":"Radiation Effects in Electronics","field":"Engineering","cited_by":176,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fault injection; Computer science; Leverage (statistics); Resilience (materials science); Embedded system; Software fault tolerance; Compiler; Software; Abstraction layer; Fault (geology); Reliability engineering; Operating system; Engineering","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":[0.0003152644,0.0001022622,0.000125721,0.00006293939,0.00006548201,0.00001540636,0.0001547081,0.00007779706,0.00001019677],"category_scores_gemma":[0.0003912751,0.00007516739,0.00005275426,0.0001314049,0.00001696755,0.0001346109,0.00001154165,0.0001115742,0.000004990201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006071387,"about_ca_system_score_gemma":0.00001154133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006348704,"about_ca_topic_score_gemma":0.00009751945,"domain_scores_codex":[0.9994017,0.00002720365,0.0001883492,0.0001025108,0.0001052532,0.0001749188],"domain_scores_gemma":[0.9990715,0.0005539306,0.00005276353,0.0002338101,0.00007050517,0.00001752399],"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":[0.00002413579,0.00002784294,0.0001360878,0.0003725618,0.00009775421,8.123076e-8,0.0003850274,0.5239225,0.02429909,0.04981785,0.01029396,0.3906231],"study_design_scores_gemma":[0.0002245584,0.0001348392,0.001008562,0.00002790212,0.00001777536,0.000003223846,0.00003687317,0.6900561,0.2856986,0.001393001,0.02123932,0.0001592268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1029407,0.00006375206,0.8937274,0.0001332884,0.0003317482,0.0005389173,0.00001294307,0.0006212175,0.001630004],"genre_scores_gemma":[0.9884633,0.00001516187,0.01111961,0.00005018126,0.0001147016,0.00009340673,0.00001101674,0.00003039551,0.0001022379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8855225,"threshold_uncertainty_score":0.3065237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02419333221403921,"score_gpt":0.2780336706396207,"score_spread":0.2538403384255815,"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."}}