{"id":"W2138270590","doi":"10.1109/hase.2007.39","title":"Improving Reliability and Safety by Trading off Software Failure Criticalities","year":2007,"lang":"en","type":"article","venue":"","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Fault tolerance; Reliability engineering; Computer science; Failure rate; Reliability (semiconductor); Voting; Software quality; Software fault tolerance; Constraint (computer-aided design); Fault (geology); Class (philosophy); Process (computing); Software; Life-critical system; Distributed computing; Software development; Engineering; Artificial intelligence; Programming language","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":[0.002571538,0.0001580188,0.0002419816,0.0001050023,0.0003100995,0.0002904576,0.0005670699,0.0001188248,0.00008486257],"category_scores_gemma":[0.00180642,0.0001332098,0.00009815407,0.0004611938,0.0002394223,0.0006813787,0.000335738,0.0002898011,0.00001054113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009663727,"about_ca_system_score_gemma":0.00006515797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002537485,"about_ca_topic_score_gemma":0.0000550325,"domain_scores_codex":[0.9977946,0.0001058563,0.0003944014,0.0006371105,0.0004933779,0.0005746588],"domain_scores_gemma":[0.9971701,0.001718185,0.00003374289,0.0006187703,0.0001757088,0.0002834749],"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":[0.00004782659,0.0002962723,0.05160944,0.0004282545,0.00005708329,0.00003220476,0.00133325,0.00001310367,0.002624057,0.04983427,0.006780276,0.8869439],"study_design_scores_gemma":[0.004795221,0.001246159,0.05894072,0.0003428595,0.0001551436,0.000253983,0.007075208,0.5156348,0.06048318,0.1500735,0.195938,0.005061194],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05685803,0.0003671031,0.9393388,0.002303228,0.000047697,0.0001253909,0.000005925996,0.000355804,0.0005980427],"genre_scores_gemma":[0.8666101,0.00003864768,0.1323811,0.0003440615,0.00004521114,0.000004952051,0.000004086129,0.000009428794,0.0005624548],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8818828,"threshold_uncertainty_score":0.5432138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006764259716144,"score_gpt":0.2612918160596365,"score_spread":0.2512241734624751,"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."}}