MétaCan
Menu
← Back to cohort
Record W6891637453 · doi:10.4224/8zcj-j636

User's Guide: National Energy Code of Canada for Buildings 2020

2024· standard· en· W6891637453 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2024
Typestandard
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBuilding codeCode (set theory)HVACEnergy (signal processing)Complement (music)Efficient energy useEnvelope (radar)Key (lock)

Abstract

fetched live from OpenAlex

The User's Guide – National Energy Code of Canada for Buildings 2020 is designed to complement the National Energy Code of Canada for Buildings (NECB) 2020 by providing background information as well as detailed examples and calculations. This edition of the User's Guide has been updated to • introduce energy performance tiers, which provide a flexible compliance framework for achieving higher levels of energy efficiency in buildings, • include additional examples of determining the thermal characteristics of building envelope assemblies, • provide guidance on whole building airtightness testing, • describe the six different compliant HVAC systems, and • explain compliance using whole-building energy modeling. The User's Guide serves as a reference tool for those involved in building design, construction, or regulation. It explains the NECB's provisions and includes examples to assist users in understanding energy-efficient design. The guide can also be used as a resource for educators and trainers when instructing students and professionals.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.107
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.009
Science and technology studies0.0030.001
Scholarly communication0.0050.003
Open science0.0040.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1070.091

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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueNPARC→French-language works237,207→