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Record W4251751231 · doi:10.32920/ryerson.14665347.v1

Assessment of load bearing clay brick masonry for analyzing long-term durability through field measurement and visual review

2021· preprint· en· W4251751231 on OpenAlexaboutno aff
Blair E. Williams

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBrickGeotechnical engineeringDurabilityMasonryTileLoad bearingFrost (temperature)Materials scienceEngineeringStructural engineeringComposite material

Abstract

fetched live from OpenAlex

This thesis examines a load bearing clay brick century home research house in Toronto (Canada) which has recently undergone the addition of polyurethane foam insulation on all interior sides of the exterior clay brick load bearing walls, increasing the insulating value in areas to RSI 7.9 W/m2K, on average. This study introduces and advances techniques to create high-resolution stitched mosaic images of the elevations to visually document the current physical condition of the brick. The critical saturation point was used to determine the capabilities of the clay brick masonry to resist freeze-thaw damage by way of frost dilatometry testing and compared to measurements taken by in-situ moisture content sensors in the brick masonry. This project also reveals how bricks expand and deteriorate in non-uniform manner during saturated three-dimensional dilatometry testing.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.069
GPT teacher head0.390
Teacher spread0.321 · 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 designObservational
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

Citations6
Published2021
Admission routes1
Has abstractyes

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