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Record W1972125366 · doi:10.3141/2441-09

Methodology for Identifying Zero-Stress Time for Jointed Plain Concrete Pavements

2014· article· en· W1972125366 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2014
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsUniversity of Alberta
FundersPennsylvania Department of Transportation
KeywordsSlabGeotechnical engineeringGeologyCementStructural engineeringStress (linguistics)Temperature gradientMaterials scienceEngineeringComposite materialPhysicsMeteorology

Abstract

fetched live from OpenAlex

This study focused on identifying the zero-stress time (TZ) in jointed plain concrete pavements (JPCPs). TZ is the time when the concrete slab is sufficiently strong to deform (thermally expand or contract and thus curl) despite the existing external restraints, including the friction at the base-slab interface. It is critical to be able to identify TZ so that the temperature gradient present in the slab at TZ, known as the built-in temperature gradient, can be characterized. In this study, TZ was established through the instrumentation of 36 concrete slabs in four JPCP construction projects. Strain-temperature behavior in each slab was used to identify TZ. The slabs in each project were paved at different times of the day (morning, noon, early afternoon, and late afternoon) to investigate the effects of the ambient curing conditions on TZ. The degree of hydration at TZ (α TZ ) was established for each slab. The field data were used in the development of a model for predicting α TZ as a function of the concrete water-to-cement ratio, unit weight, early-age elastic modulus, and slab thickness.

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.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.429
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.208
GPT teacher head0.407
Teacher spread0.199 · 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