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Record W4206993953 · doi:10.1109/tr.2021.3104692

IEEE Reliability Society

2021· article· en· W4206993953 on OpenAlexfundno aff

Bibliographic record

VenueIEEE Transactions on Reliability · 2021
Typearticle
Languageen
FieldEngineering
TopicSafety Systems Engineering in Autonomy
Canadian institutionsnot available
FundersSingapore Management UniversityUniversidade de CoimbraUniversidade de São PauloXidian UniversitySichuan UniversityUniversidad de MurciaQueen's UniversityNorthwestern Polytechnical UniversityCentre National de la Recherche ScientifiqueChinese Academy of SciencesBeihang UniversityNational University of SingaporeMicrosoft ResearchNorthwestern UniversityNanjing UniversitySouthern Methodist UniversityUniversity of Hong KongInstitute of Electrical and Electronics EngineersTU Graz, Internationale Beziehungen und MobilitätsprogrammeUniversity of Alberta
KeywordsReliability engineeringReliability theoryReliability (semiconductor)Computer scienceEngineeringFailure ratePhysics

Abstract

fetched live from OpenAlex

of members with professional interest in product assurance.The Society is concerned with reliability, quality, and effectiveness of processes, hardware, systems, and software, and with related topics such as product liability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.877
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1230.113

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.208
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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