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Record W4230011546 · doi:10.1109/ias.2004.1348776

System reliability worth assessment using the customer survey approach

2004· article· en· W4230011546 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

VenueConference Record of the 2004 IEEE Industry Applications Conference, 2004. 39th IAS Annual Meeting. · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBackupReliability (semiconductor)Customer satisfactionWork (physics)BusinessCustomer serviceService (business)Operations managementComputer scienceMarketingPower (physics)Engineering

Abstract

fetched live from OpenAlex

A very popular method utilized in quantifying the benefit of power delivery service reliability is to estimate the customer monetary losses associated with power supply interruptions by collecting data with customer surveys. MidAmerican Energy Company, a Midwest utility, recently performed surveys of its customers in the residential, commercial, industrial and company/organization sectors. This work presents the industrial and commercial customer results of these surveys with primary focus on the cost results. The results of this study are compared with the results of other studies performed in high cost areas of the United States east and west coasts. This is the First ever study of this nature performed for the electrical customers in the United States Midwest region. Methodological differences in study design compared to coastal surveys are discussed. The major contribution of this paper is that particulars of Midwest customers compared to customers of coastal utilities are noted, the impact on customers with backup supply is identified, a suggested approach to enhancing customer satisfaction due to advance warning on outages is recommended, and relatively high survey response return rates are elaborated. The customer damage functions derived from the survey results are being routinely used in power delivery project justifications in annual delivery system budgeting process.

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)0.002
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
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 head0.032
GPT teacher head0.267
Teacher spread0.235 · 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