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Record W2070808904 · doi:10.1109/carpi.2014.7030065

Hydro-Québec's Power Line Robotics Program: 15 years of development, implementation and partnerships

2014· article· en· W2070808904 on OpenAlexafffundabout
Serge Montambault, Nicolas Pouliot

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Line Inspection Robots
Canadian institutionsHydro-Québec
FundersHydro-Québec
KeywordsRoboticsLeverage (statistics)Artificial intelligenceEngineering managementEngineeringRobotComputer scienceManufacturing engineeringSystems engineering

Abstract

fetched live from OpenAlex

This paper summarizes the work related to power line robotics over the past 15 years at Hydro-Québec's research institute (IREQ). Robotic platforms are presented as well as the inspection and maintenance systems equipping them. The paper also presents a new organizational unit recently established at IREQ and called the “Power Line Robotics Program” (PLRP). This novel structure's objective is to leverage the benefits of external collaboration and international interest in power line robotics, in order to provide Hydro-Québec with professional inspection services, manufacturing capacity and strategic funding for new developments. More recent activities related to non-destructive probes are also discussed. Examples of PLRP tasks and responsibilities are given, stating why this structure is relevant within a power utility and how it accelerates the use and benefit of robotics in the power industry.

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)0.005
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.534
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.004

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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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 designNot applicable
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

Citations14
Published2014
Admission routes3
Has abstractyes

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