{"id":"W4214814595","doi":"10.1109/tr.2022.3154070","title":"IEEE Reliability Society","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Reliability","topic":"Safety Systems Engineering in Autonomy","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Singapore Management University; Universidade de Coimbra; Universidade de São Paulo; Xidian University; Sichuan University; Universidad de Murcia; Northwestern Polytechnical University; Queen's University; TU Graz, Internationale Beziehungen und Mobilitätsprogramme; University of Hong Kong; Centre National de la Recherche Scientifique; Chinese Academy of Sciences; Beihang University; National University of Singapore; Microsoft Research; Northwestern University; Nanjing University; Southern Methodist University","keywords":"Reliability engineering; Reliability theory; Reliability (semiconductor); Computer science; Engineering; Failure rate; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008627241,0.0003318062,0.0003487267,0.0000870297,0.0004131999,0.00002446798,0.0003834336,0.0001288858,0.0006183815],"category_scores_gemma":[0.000009035412,0.0003851858,0.0004644502,0.0005672905,0.00009026458,0.0001489595,0.000002491271,0.001098727,0.0000900437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001380402,"about_ca_system_score_gemma":0.0000677369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007267356,"about_ca_topic_score_gemma":0.000005082677,"domain_scores_codex":[0.9978272,0.0001236783,0.0005611178,0.0005423863,0.0004775255,0.0004681318],"domain_scores_gemma":[0.9982767,0.0002734303,0.00003961633,0.001202139,0.00005808166,0.0001500147],"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":[0.00001639924,0.0001641928,0.00004878973,0.0001340133,0.00004809015,0.00000156357,0.0003363659,0.9933058,0.001321061,0.00001113706,0.001993329,0.002619254],"study_design_scores_gemma":[0.001224708,0.000272231,0.002956229,0.00003167814,0.0000969336,0.00004569691,0.0003890356,0.873167,0.028834,0.0003402248,0.09136627,0.001275967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2246134,0.00006356804,0.7596245,0.0002424517,0.007844104,0.0008963566,0.0002766425,0.003033724,0.00340528],"genre_scores_gemma":[0.9961661,0.00001843355,0.002506951,0.00008580988,0.0000736589,0.0006865964,0.000004521431,0.00007011667,0.0003878011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7715527,"threshold_uncertainty_score":0.99986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008358238747275456,"score_gpt":0.2000864664567832,"score_spread":0.1917282277095077,"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."}}