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Record W2941140592 · doi:10.1177/0361198119845655

Laboratory Investigation of Foam Grout Performance under Freeze and Thaw Conditioning

2019· article· en· W2941140592 on OpenAlexaff
Vinicius Afonso Velasco Rios, Leila Hashemian

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2019
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGroutCementCompressive strengthMaterials scienceComposite materialGeotechnical engineeringMoistureFoam concreteThermal insulationForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Foam grout is a fluid, self-leveling, and lightweight material with excellent load spreading and thermal insulation properties. These properties have contributed to foam grout being considered over its regular cement/water grout counterparts for many projects. Although applied in many successful cases, not much has been done to compare foam and regular grout behavior in cold regions. This research focused on the compressive strength of both materials before and after freeze/thaw cycles. Specimens were cured for different durations in a moisture room and conditioned for diverse freezing/thawing cycles to assess short- and long-term performance. The impact of immediate freezing was also evaluated for both materials. Foam grout’s ability to resist cold environments was explained using test results and visual analysis. At the end of the process, a material cost versus strength analysis was conducted with the intent of providing a reliable source of information when selecting materials to fulfill minimum industry specifications.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.042
GPT teacher head0.301
Teacher spread0.260 · 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
Published2019
Admission routes1
Has abstractyes

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