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Record W6947932333 · doi:10.4224/zy3s-rk91

Code national de prévention des incendies : Canada : 2020

2022· standard· en· W6947932333 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2022
Typestandard
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsFlammable liquidDemolitionFire protectionFire safetyPlan (archaeology)Commission

Abstract

fetched live from OpenAlex

The National Fire Code of Canada (NFC) 2020, developed by the Canadian Commission on Building and Fire Codes and published by the National Research Council of Canada, sets out technical requirements for: • activities related to the construction, use or demolition of buildings and facilities • the condition of specific elements of buildings and facilities • the design or construction of specific elements of facilities related to certain hazards • protection measures for the current or intended use of buildings Nearly 40 technical changes have been incorporated in this new edition, improving the level of safety, health and fire protection provided by the Code, and expanding the NFC into new areas. Significant changes in the NFC 2020 • Technical requirements for large farm buildings are added, which address the inspection of mechanical equipment and electrical systems, the control of flammable gases and vapours, and the storage of flammable or combustible liquids. • Fire safety plan requirements are consolidated to facilitate compliance and enforcement. • Classifications are established for 5 widely used water-miscible liquid mixtures to ensure that appropriate fire safety measures are applied in their storage, handling, use and processing. • Measures are included to address fire safety during the construction of encapsulated mass timber buildings.

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)0.012
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 score0.056
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0050.002
Scholarly communication0.0060.002
Open science0.0040.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0410.026

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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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