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Record W3203400824 · doi:10.2118/204487-ms

Permanent Magnet Motor Safety

2021· article· en· W3203400824 on OpenAlexaff
Barry Nicholson, Carlos Yicon, Dennis Harris, Richard Delaloye

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsTroubleshootingInstallationOperations managementBusinessRisk analysis (engineering)Computer scienceComputer securityEngineeringReliability engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract As Permanent Magnet Motors (PMMs) become more widely used because of their many benefits, awareness of the potential safety hazards arising from their differences from Induction Motors (IMs) is important. Due to their construction, the magnetic field presence is always "on" with PMM – even when not under energized electrical energy. PMMs are AC generators when freely rotating forward or backward. Elevated safety consciousness is needed to avoid serious injury or fatality when working with PMMs. This paper presents operational procedures for installing, pulling, troubleshooting, and handling PMMs with a focus upon safety. Hazards have been identified, and some mitigations are recommended to eliminate the potential danger and bring awareness to the petroleum industry (and others) to ensure that all workers go home safely. The observations presented in this paper came directly from field experience with operators, equipment manufacturers, and service providers.

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)0.003
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: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.007

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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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