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Record W4232559208 · doi:10.32920/ryerson.14660886

An Investigation on the Critical Degree of Saturation of Half Brick Samples via the Frost Dilatometry Methodology

2021· preprint· en· W4232559208 on OpenAlexaff
Javeriya Hasan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsSciencetech (Canada)
Fundersnot available
KeywordsBrickSaturation (graph theory)Frost (temperature)Degree (music)MoistureDegree of saturationGeotechnical engineeringMaterials scienceWater contentMineralogyComposite materialSoil scienceGeologyMathematicsPhysicsSoil water

Abstract

fetched live from OpenAlex

An Investigation on the Critical Degree of Saturation of Half Brick Samples via the Frost Dilatometry Methodology By Javeriya Hasan Master of Building Science in the Program of Building Science 2019 An assessment of freeze-thaw deterioration of bricks necessitates predicting the moisture content at which frost decay occurs, whereby this is called the critical degree of saturation (Scrit). The study involved performing frost dilatometry testing of eight half-brick samples. Strains along the x, y and z axes of samples were measured, whereby the results show that trends of frost decay were non-uniform along certain axes. However, along the z-axis, brick sample types 305-EB4, 295AF4, 297-EB2 showed Scrit values of 81%, 90% and 77.5% respectively, which were comparable to the slices’ Scrit, which were at 84.4%, 88.1% and 77.5% respectively. Similarly, for brick sample type 349-ER1, the Scrit at its x-axis was 92%, which was near to its slice’s Scrit, at 87.3%. Sample types 60 and 295-F2 showed differences as high as 17% in their Scrit values, at 56% and 88% respectively, compared to their slices, which were at 73.4% and 78.4%.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.229
GPT teacher head0.315
Teacher spread0.086 · 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 teacher head, not a consensus.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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