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Record W2002477695 · doi:10.1109/2943.811077

Industrial Facilities Gain New Area Classification Guidelines

2000· article· en· W2002477695 on OpenAlexaboutno aff
D Bishop, David Jagger, J.E. Propst

Bibliographic record

VenueIEEE Industry Applications Magazine · 2000
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsFlammable liquidHazardous wasteScope (computer science)PetroleumInstallationNational Electrical CodeEngineeringForensic engineeringClass (philosophy)Waste managementComputer scienceCivil engineeringArchitectural engineeringMechanical engineeringArtificial intelligenceElectrical engineeringGeology

Abstract

fetched live from OpenAlex

Both the United States National Electrical Code (NEC) and the Canadian Electrical Code (CEC) provide special rules for installing electrical equipment in hazardous (classified) locations. Hazardous locations are those locations where fire or explosion hazards may exist due to flammable gases or vapors, flammable liquids, combustible dust, or easily ignitible fibers or flyings. Only Class I materials (gases and vapors) are within the scope of American Petroleum Institute (API) RP500 and RP505. These recommended practices offer those in the petroleum industry an opportunity to standardize area classification drawings-both for drawings using the Division method of area classification and for drawings using the Zone method of area classification. Good engineering judgment must be used with RP500 and RP505, but guidelines provided should minimize differences of classifications by qualified individuals classifying the same or similar locations. This article provides an overview of the two recommended practices including outlines of tables of content, but primarily emphasising the substantive changes and additions.

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)0.022
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.114
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.008
Science and technology studies0.0030.001
Scholarly communication0.0050.005
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1140.082

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 head0.092
GPT teacher head0.292
Teacher spread0.200 · 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
GenreOther

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

Citations2
Published2000
Admission routes1
Has abstractyes

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