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Record W4399765523 · doi:10.32920/26052421.v1

Changes in Subgrade Insulation Conductivity With Varying Moisture Content

2024· preprint· en· W4399765523 on OpenAlexaffabout
Lauren Asher

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSubgradeWater contentConductivityGeotechnical engineeringEnvironmental scienceMoistureMaterials scienceComposite materialGeologyPhysics

Abstract

fetched live from OpenAlex

The climate is rapidly changing, raising the groundwater level and causing more severe flooding. As flood waters rise, they saturate the soil and penetrate foundations. In Canada, there are two ways of insulating a foundation: externally against the soil or internally, like in a wall assembly. The saturation of external insulation by flood waters will change its thermal conductivity, but the effects of cyclic wetting and drying have not been well documented. There are two aspects to the study of this impact, WUFI simulation and lab testing. Three types of insulation were used in the lab testing, extruded polystyrene (XPS), closed-cell polyurethanesprayfoam,and rockwoolmineral wool,whichcanall be usedinground contact.Thepurpose is to determine if insulation can return to its pre-wetted thermal conductivity after several flooding events. The results are promising, but this topic will need to be studied over a longer period.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.000

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 head0.031
GPT teacher head0.216
Teacher spread0.185 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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