MétaCan
Menu
Back to cohort
Record W2165778560

Comparison of two methods for evaluating the effects of maintenance on component and system reliability

2004· article· en· W2165778560 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE International Conference on Probabilistic Methods Applied to Power Systems · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsnot available
Fundersnot available
KeywordsReliability engineeringReliability (semiconductor)Component (thermodynamics)Maintenance engineeringComputer scienceFailure ratePreventive maintenanceElectric power systemPower (physics)Engineering
DOInot available

Abstract

fetched live from OpenAlex

Two recently proposed methods for evaluating the effects of various maintenance policies on the reliability and operating costs of electric power systems are compared. Both programs, the one developed in Canada and the other in Sweden, first generate a priority list of components whose failures have the highest effect on system reliability, then examine the failure rates of the components on the top of the list when various maintenance policies are applied. Finally, reliability indices for the whole system are computed with the critical components represented by the failure rates corresponding to the various policies. This way, maintenance policies can be selected either to achieve the highest system reliability or the lowest operating costs. The approach is illustrated in a numerical example where both the similarities of, and the differences between, the two methods can be recognized. Comments are made on the reasons for the differences

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.431
Teacher spread0.350 · 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