MétaCan
Menu
Back to cohort
Record W2144683210 · doi:10.1109/rams.2004.1285431

Pioneers of the reliability theories of the past 50 years

2004· article· en· W2144683210 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicStatistical Distribution Estimation and Applications
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsReliability theoryReliability (semiconductor)Fault tree analysisComputer scienceQueueing theoryReliability block diagramTree diagramWeibull distributionTheoretical computer scienceBayesian probabilityMathematicsReliability engineeringStatisticsArtificial intelligenceFailure rateEngineering

Abstract

fetched live from OpenAlex

This paper is dedicated to all the researchers for their contributions in reliability theories in the past 50 years. The paper provides a summary on the pioneers of reliability theories, and how their works placed a great influence on our reliability analysis today. This is also a survey paper on reliability theories and methods. The information provided in this paper is mostly based on literatures found first hand to provide as much a neutral view as possible. However, some of the information is adopted from Refs. 1-4. Area of interest in the reliability analysis included representation of reliability parameters, renewal theory, coherent structure, diagram-based models, theoretical methods, and other miscellaneous techniques. Diagram based models included block diagrams, fault tree analysis (FTA), event tree analysis, and flowgraphs. Theoretical methods included queueing theory, asymptotic analysis, Boolean algebra, Bayesian method, Monte Carlo simulation, optimization techniques. Miscellaneous methods that cannot be classified in any of the categories are also provided. Looking back in the last century, a lot of the contributions to reliability research were done in the last 50 years. Weibull, Epstein and Sobel had made a significant influence on the distribution functions we used today. Lotka, Campbell, Feller, Cox, Smith, Barlow, Proschan, Hunter, Marshall, Esary, Gnedenko, Belyaev, and Solov'yev had advanced the theories for reliability. Takacs' paper in sojourn time provided an initiative to the asymptotic studies. Birnbaum started a whole family on component importance measure for coherent structure.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.566
Threshold uncertainty score0.169

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.314
Teacher spread0.289 · 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