MétaCan
Menu
Back to cohort
Record W2077970824 · doi:10.1515/secm.2009.16.2.99

Modeling of Delamination Initiation and Propagation in Composite Laminates Under Monotonie Tensile Loading Using the Progressive Damage Modeling Technique

2009· article· en· W2077970824 on OpenAlexaff
Pierre-Luc Vachon, Vladimir Braïlovski, Patrick Terriault

Bibliographic record

VenueScience and Engineering of Composite Materials · 2009
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceDelamination (geology)Composite numberComposite materialUltimate tensile strengthComposite laminatesStructural engineering

Abstract

fetched live from OpenAlex

Article Modeling of Delamination Initiation and Propagation in Composite Laminates Under Monotonie Tensile Loading Using the Progressive Damage Modeling Technique was published on June 1, 2009 in the journal Science and Engineering of Composite Materials (volume 16, issue 2).

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.251
Teacher spread0.234 · 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 designSimulation or modeling
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

Citations3
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueScience and Engineering of Composite MaterialsSame topicMechanical Behavior of CompositesFrench-language works237,207