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Record W4230914751 · doi:10.32920/ryerson.14653866.v1

A Method for Determining the Relationship Between Increasing Insulation and Potential Freeze Thaw Damage in Brick Masonry Walls

2021· preprint· en· W4230914751 on OpenAlexaffabout
Braden M. Johnson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMasonryBrickEngineeringGeotechnical engineeringCivil engineeringStructural engineeringForensic engineeringArchitectural engineering

Abstract

fetched live from OpenAlex

When considering insulation retrofits, property limit distances and setbacks make interior insulation of residential homes the only viable option. When pursuing an interior insulation retrofit the potential for brick masonry freeze thaw damage needs to be considered. Studying the impacts of an interior insulation retrofit Pre-World War 2 residential building in Toronto, Ontario, a comparison of the retrofitted building using WUFI against 8 other insulation types was completed to determine if the change of insulation affects the potential for freeze thaw damage. Based on the results of the WUFI analysis the answer would be yes. The insulation type and R value does have an impact brick masonry freeze thaw resistance. However this relationship is general and not linear. The method provided shows that if critical saturation (SCRIT) is known predictive modeling on the impacts of interior insulation on the moisture performance of the brick masonry wall can be used.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.286
Teacher spread0.237 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2021
Admission routes2
Has abstractyes

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