MétaCan
Menu
Back to cohort
Record W4394750731 · doi:10.14359/51740374

Chemical Detection of Expansion Susceptibility of Concrete

2024· article· en· W4394750731 on OpenAlexaboutno aff
Ronald Lichtenwalner, Joseph T. Taylor

Bibliographic record

VenueACI Materials Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsnot available
FundersFederal Highway AdministrationNorth Carolina Department of TransportationU.S. Department of Transportation
KeywordsMaterials scienceComposite materialStructural engineeringForensic engineeringGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

This experimental study evaluated the correlation between measured concrete expansion from a modified version of the miniature concrete prism test (MCPT) with the concentration of chemical markers leached from the prisms into an alkaline soak solution.Fifteen concrete mixture designs were tested for expansion and soak solution concentrations over time.The changes in expansion and soak solution concentrations were found to correlate well even with variations in alkali loading and substitution of cement with Class F fly ash.A model was developed to estimate the expansion potential of concrete based on an expansion reactivity index (ERI) that incorporated the concentrations of silicon, sulfate, calcium, and aluminum.The relationship between ERI and expansion was then used to identify potentially expansive concrete mixtures using the ERI of cores taken from a structure exhibiting potential alkalisilica reaction (ASR) expansion and concrete cylinders matching the mixture designs of the MCPT specimens.

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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.013
GPT teacher head0.224
Teacher spread0.211 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueACI Materials JournalSame topicConcrete Properties and BehaviorFrench-language works237,207