{"id":"W2969446929","doi":"10.1109/dsn-s.2019.00012","title":"Towards Predicting the Impact of Roll-Forward Failure Recovery for HPC Applications","year":2019,"lang":"en","type":"article","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Probabilistic logic; Scheme (mathematics); Reliability engineering; Point (geometry); Risk analysis (engineering); Distributed computing; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002194821,0.001239217,0.0006332389,0.001690361,0.0002693048,0.0009793041,0.0008475181,0.001620085,0.001049529],"category_scores_gemma":[0.01784691,0.0003668778,0.000463962,0.000792458,0.0006916957,0.001728946,0.0007494511,0.001413578,0.000354651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005634742,"about_ca_system_score_gemma":0.0006802055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004453637,"about_ca_topic_score_gemma":0.003029334,"domain_scores_codex":[0.9994429,0.0001695346,0.00003427642,0.0000936125,0.000181882,0.00007772941],"domain_scores_gemma":[0.9869578,0.009386287,0.001324391,0.0008626013,0.00118505,0.0002838236],"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":[0.0001565282,0.0000806159,0.01209589,0.00005619188,0.00003401884,0.00003409959,0.00002166882,0.9665187,0.003117619,0.0006039059,0.0003133309,0.01696756],"study_design_scores_gemma":[0.000001960634,0.0000237017,0.001464401,0.000004048852,0.00000438091,0.000007756092,0.000007513756,0.9961478,0.00121536,0.001064476,0.00005499744,0.000003696981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5562072,0.001105068,0.4379993,0.0006612127,0.00007555309,0.0001012471,0.0006575162,0.001965084,0.001227848],"genre_scores_gemma":[0.9570023,0.0002704284,0.04151098,0.0000397159,0.0000511262,0.00003617147,0.0003766168,0.00009875294,0.0006139001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004453637,"threshold_uncertainty_score":0.01160747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008688041940521961,"score_gpt":0.264289258437508,"score_spread":0.255601216496986,"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."}}