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Record W7132977401

Hygrothermal design methodology for exterior wood-frame walls in Canadian low-rise residential construction

2007· dissertation· W7132977401 on OpenAlexfundaboutno aff
Svetlana Valeryevna Melnichuk

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsCold climateDesign methodsBuilding codeDesign elements and principlesBuilding insulationEngineered wood
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a design methodology for the satisfactory long-term hygrothermal performance of exterior wood-frame walls in low-rise residential construction as constructed in the cold climate of Canada. Two wall types are considered: a 38mm x 140mm brick-clad wood stud wall insulated internally with fibreglass and externally with extruded polystyrene, and a 38mm x 140mm EIFS-clad wood stud wall insulated internally with fibreglass and externally with expanded polystyrene. The hygrothermal performance of walls exposed to simulated climates in Halifax, Ottawa, Toronto, Saskatoon and Vancouver is examined. The methodology uses an advanced hygrothermal model hygIRC 1-D (NRC) to simulate the performance of the wall and analyze the results. Quasi-limit state design principles are applied. The maximum amounts of extra added external insulation necessary for satisfactory long-term hygrothermal performance are determined for both wall types in all five cities. The thesis makes recommendations for the National Building Code of Canada.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.946
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.347
Teacher spread0.297 · 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
GenreMethods

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
Published2007
Admission routes2
Has abstractyes

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