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Record W2426451253 · doi:10.5006/c2016-07393

AC Interference Risk Ranking: Case Study

2016· article· en· W2426451253 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
TopicElectrical Fault Detection and Protection
Canadian institutionsStantec (Canada)Cochrane
Fundersnot available
KeywordsInterference (communication)Ranking (information retrieval)Electromagnetic interferenceComputer scienceMaterials scienceArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

Abstract As utility corridors become increasingly congested, AC interference on pipelines due to collocation with high voltage AC (HVAC) transmission powerlines continues to be a growing concern. Many pipeline operators have large quantities of existing pipeline infrastructure that has not been fully assessed to determine whether it is at risk due to AC interference. The primary risks on these pipelines under powerline steady-state conditions are safety and AC corrosion. This paper is a case study of a project involving AC interference risk ranking of over 6,400 miles (10,300 km) of existing transmission piping operated by one of the largest combination gas and electric utilities in the United States. The scope of this project is to identify the transmission pipelines that are at greatest risk due to steady-state AC interference, to prioritize them based on the severity of risk, and to determine what further action is required. Once the ranking is completed, it is envisioned that AC interference studies, and the design and implementation of mitigation and monitoring systems will be performed on the at risk pipeline systems in order of priority as part of a multi-year program.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.368

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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