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Record W2002477695 · doi:10.1109/2943.811077

Industrial Facilities Gain New Area Classification Guidelines

2000· article· en· W2002477695 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.761
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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