{"id":"W4301385812","doi":"","title":"Hard faults and soft errors: possible numerical remedies in linear algebra solvers","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Linear algebra; Computer science; Algebra over a field; Numerical linear algebra; Algorithm; Applied mathematics; Linear system; Mathematics; Pure mathematics; Mathematical analysis; Geometry","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":[0.00285968,0.0001813848,0.0002512759,0.0001348108,0.0001820532,0.0001300721,0.000917308,0.00008739854,0.00003058226],"category_scores_gemma":[0.001617296,0.00013681,0.00007293141,0.0005729999,0.0002184547,0.0004709307,0.0005955835,0.0001758838,0.00003959791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004943095,"about_ca_system_score_gemma":0.00008094352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003113917,"about_ca_topic_score_gemma":0.00007038059,"domain_scores_codex":[0.996487,0.001888922,0.000338951,0.0005973558,0.0003075375,0.000380248],"domain_scores_gemma":[0.9966574,0.001615566,0.000150165,0.0009496364,0.000416268,0.0002109451],"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":[0.00001098806,0.0003258184,0.008691865,0.00002491065,0.00002251871,0.00001537662,0.004658805,0.00000406406,0.01816645,0.06980265,0.0004634153,0.8978131],"study_design_scores_gemma":[0.006499086,0.00001476085,0.1318141,0.0039675,0.00004173602,0.0001168026,0.0004814883,0.3698818,0.3067015,0.1026446,0.07518978,0.00264692],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03070684,0.0002852783,0.9418399,0.02433636,0.0001720246,0.0001322299,0.000004892976,0.0001687458,0.002353758],"genre_scores_gemma":[0.2679161,0.0002406496,0.7280653,0.0002236081,0.00002056137,0.00002009588,0.00000373387,0.00001723539,0.003492739],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8951662,"threshold_uncertainty_score":0.5578949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603705846315263,"score_gpt":0.2482776919323049,"score_spread":0.2322406334691523,"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."}}