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Record W6891684666 · doi:10.4224/y3ef-tg80

Code national du bâtiment : Canada : 2020

2022· standard· en· W6891684666 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2022
Typestandard
Languageen
FieldMedicine
TopicOcular and Laser Science Research
Canadian institutionsnot available
Fundersnot available
KeywordsDemolitionBuilding codeEfficient energy useFire protectionCommissionOccupancy

Abstract

fetched live from OpenAlex

The National Building Code of Canada (NBC) 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 the design and construction of new buildings, as well as the alteration, change of use and demolition of existing buildings. Over 280 technical changes have been incorporated in this new edition, improving the level of safety, health, accessibility, fire and structural protection, and energy efficiency provided by the Code, and expanding the NBC into new areas. Significant changes in the NBC 2020 • Technical requirements for large farm buildings are added, which address fire protection, occupant safety, structural design, and heating, ventilating and air-conditioning. • Encapsulated mass timber construction is introduced, enabling the construction of wood buildings with up to 12 storeys. • Accessibility requirements are updated to reduce barriers related to anthropometrics, plumbing facilities, signage, entrances and elevators. • Design requirements for evaporative equipment are revised to minimize the growth and transmission of Legionella and other bacteria. • A home-type care occupancy is introduced to allow safe and affordable care in a home-type setting. • Energy performance tiers are established to provide a framework for achieving higher levels of energy efficiency in housing and small 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)0.004
metaresearch head score (Gemma)0.010
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 score0.142
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0050.002
Scholarly communication0.0070.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.1420.104

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 head0.017
GPT teacher head0.299
Teacher spread0.282 · 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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Same venueNPARCSame topicOcular and Laser Science ResearchFrench-language works237,207