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Record W4401755634 · doi:10.15554/pcij69.5-02

Creep and Shrinkage of Nonproprietary Ultra-High-Performance Concrete

2024· article· en· W4401755634 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePCI Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsShrinkageCreepMaterials scienceComposite materialStructural engineeringForensic engineeringEngineering

Abstract

fetched live from OpenAlex

This paper presents the results of the experimental evaluation of four nonproprietary ultra-high-perfor¬mance concrete (UHPC) mixture proportions current¬ly being used for industrial applications by various precast concrete producers across the United States and Canada. The main objective of this research was to acquire data about the effects that creep and shrinkage phenomena produced with UHPC materials. Shrinkage was assessed by the ASTM C157 testing method modified by ASTM C1865 and ASTM C1698. Creep was evaluated by the ASTM C512 testing method modified by ASTM C1856. Results for creep and shrinkage strains and creep coefficient are pre¬sented and discussed. Comparisons with conventional concrete are also made. This detailed characterization of creep and shrinkage properties of the nonproprietary UHPC mixture proportions advances the understanding of UHPC materials and phenomena and offers useful information for further research on applications of UHPC for prestressed concrete structural components.

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)0.000
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 score0.322
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.193
Teacher spread0.184 · 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