MétaCan
Menu
Back to cohort
Record W2169047150 · doi:10.1109/arms.1988.196462

Common-cause failures in repairable systems

2003· article· en· W2169047150 on OpenAlexaff
B.S. Dhillon, Subramanyam N. Rayapati

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReliability engineeringReliability (semiconductor)Common cause failureComputer scienceReliability theoryMean time between failuresVariance (accounting)Redundancy (engineering)Common cause and special causeEngineeringStatisticsFailure rateMathematics

Abstract

fetched live from OpenAlex

Eight models are presented for performing reliability analysis of repairable and nonrepairable redundant systems with common-cause failures. The systems studied are redundant configurations such as parallel, k-out-of-n units, and standby. Repairable systems reliability, mean-time-to-failure, and variance of time to failure formulas are developed. In addition, the reliability analysis of a redundant system composed of three state devices with common-cause failures is presented. Specific plots are developed to demonstrate the effect of common-cause failures on redundant system reliability and mean time of failure.>

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.197
Teacher spread0.189 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations11
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicReliability and Maintenance OptimizationFrench-language works237,207