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Record W4399146255 · doi:10.1109/mias.2024.3395934

Doors Wide Open: Safety Beyond the Standards: The Testing of Real-World Scenarios

2024· article· en· W4399146255 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

VenueIEEE Industry Applications Magazine · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsRockwell Automation (Canada)
Fundersnot available
KeywordsDoorsEngineeringComputer scienceForensic engineeringReliability engineeringMechanical engineering

Abstract

fetched live from OpenAlex

For nearly three decades, arc-resistant, detection, and quenching technologies have been in use and have continued to evolve together with changes to the associated global standards. These arc flash-related standards dictate hardware configurations and performance characteristics based on specific testing methods. However, they primarily focus on arc testing devices with equipment doors closed and latched, which offers only one basic protection scenario. Yet, many arc flash incidents occur when doors are open, especially during troubleshooting or equipment safety assessments. This raises questions about the validity of the testing sequences and results outlined in these standard procedures when one or more doors are open. This article aims to address this issue by proposing modifications to standard testing methods to better simulate real-world scenarios, where doors are often open during inspections and maintenance situations. Additionally, it will review the global standards for active arc fault mitigation, particularly focusing on regions adhering to IEC standards, where more rapid growth in deployment has been observed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.103
GPT teacher head0.475
Teacher spread0.372 · 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