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Record W1989042499 · doi:10.1109/tdc.2014.6863242

Determining transmission line conductor condition and remaining life

2014· article· en· W1989042499 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
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsKinectrics (Canada)
Fundersnot available
KeywordsOverhead (engineering)Computer scienceAsset (computer security)Transmission lineProcess (computing)Simple (philosophy)Line (geometry)Electric power transmissionReliability engineeringEngineeringMathematicsTelecommunicationsElectrical engineeringComputer security

Abstract

fetched live from OpenAlex

Many overhead transmission lines in North America have exceeded their expected design life. It is therefore of interest to estimate the conditions and remaining lives of conductors in order to facilitate maintenance and capital replacement planning. Determining condition or health requires considerable investments. This report investigates whether visual inspection and age are sufficient parameters for estimating the remaining life of this asset. The simple visual and age assessment is quantified by means of Health Indexing. The effectiveness of this simple assessment is measured by comparing it to a condition evaluation that is based on detailed, quantitative laboratory testing. The use of life curves for different geographical regions facilitates the process of determining remaining life. Estimated lives based on the simple and more comprehensive assessments, as well as based on chronological age are compared for different geographical regions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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

Quick stats

Citations18
Published2014
Admission routes1
Has abstractyes

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