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Record W4408626095 · doi:10.5006/mp2023_62_2-34

Case Study: Sharing an Alternating Current Mitigation System

2023· article· en· W4408626095 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMaterials performance · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsAlberta EnergyATCO (Canada)Petroleum Technology Alliance Canada
Fundersnot available
KeywordsAlternating currentCurrent (fluid)Materials scienceEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

An alternating current (AC) interference study was conducted in 2019 following a utility development with a new substation and 24 km of powerline upgrades in Alberta, Canada. The study comprised six powerlines by one utility and eight pipelines by two operators. Computer modelling showed voltage hazards under steady-state and fault conditions, susceptibility to AC corrosion, and high coating stress in the unmitigated state. A shared AC mitigation system was designed to eliminate these hazards while reducing mitigation requirements, site visits, construction footprint, environmental impact, and project costs. This article describes the design, installation, commissioning, and benefits of the shared mitigation system.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.751
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.174
GPT teacher head0.418
Teacher spread0.244 · 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