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Record W2166417224 · doi:10.1139/l09-071

Influence des rapports eau/ciment et fines/ciment sur le comportement à l’état durci du béton autoplaçant à base de matériaux locaux algériens

2009· article· fr· W2166417224 on OpenAlexvenueno aff
N. Bouhamou, Nadia Belas, Habib Abdelhak Mesbah, Raoul Jauberthie, A. Ouali, Abdelkader Mebrouki

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languagefr
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Le présent travail est une seconde étape faisant partie de notre travail de recherche sur l’influence des paramètres de composition sur le comportement des bétons autoplaçants (BAP) à l’état frais et durci. Il concerne l’étude de l’effet des rapports eau sur ciment et fines sur ciment sur le comportement du BAP à l’état durci. Plusieurs essais ont été réalisés tels que l’étalement, la boîte en L, la stabilité au tamis, le ressuage, les résistances mécaniques, le retrait libre (retrait de séchage et retrait endogène) et une étude microstructurale (caractérisation minéralogique, distributions porométriques) afin de comprendre les rôles joués par les différents constituants susceptibles d’entrer dans la formulation d’un BAP à base de matériaux locaux et chercher à mieux cerner les mécanismes qui régissaient les comportements vis-à-vis du retrait. Nous avons mis en évidence le rôle du réseau poreux et de la microstructure des hydrates. Les résultats obtenus offrent de belles perspectives pour optimiser les BAP en Algérie. Notre étude a permis de développer une variété de formulations de bétons autoplaçants répondant aux critères rhéologiques (bonne déformabilité, moins de ressuage, absence de ségrégation, meilleures performances mécaniques).

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicInnovations in Concrete and Construction MaterialsFrench-language works237,207