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Record W2021201480 · doi:10.1139/l00-026

Les bétons renforcés de fibres d'acier et la multifissuration

2000· article· en· W2021201480 on OpenAlexvenueno aff
Benoı̂t Bissonnette, Yves Therrien, R. Pleau, Michel Pigeon, François J. Saucier

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
Fundersnot available
KeywordsCrackingShrinkageMaterials scienceComposite materialUltimate tensile strengthFiber-reinforced concreteTension (geology)ReinforcementCementReinforced concreteStructural engineeringEngineering

Abstract

fetched live from OpenAlex

This paper presents the results of an investigation aimed at establishing if multiple cracking can be an intrinsic property of steel fibre reinforced concrete (SFRC) in the hardened state and identifying the conditions to obtain it systematically. For this purpose, uniaxial restrained shrinkage tests and tensile tests were performed on large-scale SFRC specimens. The parameters studied in the experimental program were the fibre content (0-100 kg/m3), the fibre geometry, and the water to cement ratio of the concrete matrix (w/c = 0.40-0.80). The test results tend to indicate that multiple cracking is not a property of SFRC as such, at least within the range of concrete matrices and fibre contents investigated and that were intended to be compatible with practical considerations. While it does not mean that fibre reinforcement is not effective in terms of crack control, it is important to be careful in the analysis of test results where the effect of the restraining and exposure conditions might have been significant.Key words: cracking, drying shrinkage, fibre-reinforced concrete, multiple cracking, repairs, restrained shrinkage, steel fibres, tension.

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)0.006
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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

Citations2
Published2000
Admission routes1
Has abstractyes

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