MétaCan
Menu
Back to cohort
Record W4241927631 · doi:10.1109/tdc.1991.169601

Aged ACSR conductors. I. Testing procedures for conductors and line items

2002· article· en· W4241927631 on OpenAlexaffabout
D.G. Havard, G. Bellamy, P.G. Buchan, H.A. Ewing, D.J. Horrocks, S.G. Krishnasamy, J. Motlis, K.S. Yoshiki-Gravelsins

Bibliographic record

VenueProceedings of the 1991 IEEE Power Engineering Society Transmission and Distribution Conference · 2002
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsElectrical conductorConductorCorrosionMaterials scienceDuctility (Earth science)Electric power transmissionNondestructive testingMetallurgyComposite materialElectrical engineeringEngineeringCreepPhysics

Abstract

fetched live from OpenAlex

Field and laboratory tests of aluminum conductor steel reinforced (ACSR) conductors and related line items from many of Ontario Hydro's older transmission lines are described. A nondestructive corrosion detector was modified for live line measurement of the loss of galvanizing from the steel cores of the ACSR conductors. Samples of conductors tested in the field have also undergone laboratory metallurgical investigation, and tests of fatigue, tensile strength, torsional ductility and electrical performance. Extensive environmental studies have identified corrosion products of ACSR conductors, the atmospheric factors responsible for corrosion, and the mechanisms by which corrosion takes place. It is concluded that the corrosion detector serves as a useful indicator of impending end of conductor life while the torsional ductility tests serve as a more precise condition indicator and can provide a guide for scheduling conductor replacement.>

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.005

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 head0.031
GPT teacher head0.215
Teacher spread0.184 · 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 designBench or experimental
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

Citations1
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the 1991 IEEE Power Engineering Society Transmission and Distribution ConferenceSame topicMechanical stress and fatigue analysisFrench-language works237,207