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Record W2319929728 · doi:10.3166/rcma.22.299-313

Vieillissement, durabilité et dégradation de matériaux composites soumis à des environnements agressifs

2012· article· fr· W2319929728 on OpenAlexvenueno aff
Marco Gigliotti

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2012
Typearticle
Languagefr
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsComposite materialMaterials scienceGradationArt

Abstract

fetched live from OpenAlex

L'AMAC a attribue le Prix Daniel Valentin 2010 a l'auteur pour son travail de recherche dans le domaine du vieillissement et de la durabilite de materiaux composites a matrice organique (CMO) soumis a des environnements agressifs et concernant, en particulier : - le couplage hygro - thermo - mecanique lie a des variations cycliques de temperature et humidite [1 - 3] et le developpement d'une technique experimentale originale - employant des plaques composites asymetriques de type 0/90 - pour le suivi et la caracterisation de ces phenomenes [6 - 9], - le couplage mecano - diffusif lie aux mecanismes de thermo oxydation a haute temperature et a haute pression [4 - 5], et la caracterisation des effets de ce couplage a differentes echelles, - le couplage electro - mecanique ayant lieu dans des materiaux composites soumis a des courant electrique d'intensite intermediaire [10] et l'effet de ce couplage sur la duree de vie des CMO. Dans cet articles une partie de ces travaux est synthetiquement resumee, les problematiques majeures liees au vieillissement des CMO sont mises en relief, les principaux verrous a lever sont presentes et des pistes pour des futurs travaux de recherche dans ce domaine sont identifiees.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.004

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 head0.046
GPT teacher head0.284
Teacher spread0.238 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicSmart Materials for ConstructionFrench-language works237,207