MétaCan
Menu
Back to cohort
Record W2914278103

Micro-CT-based analysis of fibre-reinforced composites: Applications

2018· preprint· en· W2914278103 on OpenAlexaff
Ilya Straumit, İsmet Baran, Larissa Gorbatikh, László Farkas, Christine Hahn, K. Ilin, Jan Ivens, Larry Lessard, Y. Liu, Ngoc Ha Nguyen, Anna Matveeva, Mahoor Mehdikhani, Oksana Shishkina, Jeroen Soete, Jun Takahashi, Dirk Vandepitte, Dmytro Vasiukov, Yi Wan, E. Winterstein, Martine Wevers, Stepan Vladimirovitch Lomov

Bibliographic record

VenueUniversity of Twente Research Information · 2018
Typepreprint
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsMcGill University
FundersToyota Motor EuropeJapan Society for the Promotion of ScienceVlaamse regeringHorizon 2020 Framework ProgrammeAgentschap Innoveren en OndernemenBộ Giáo dục và Ðào tạoChina Scholarship CouncilKU LeuvenFonds Wetenschappelijk Onderzoek
KeywordsComposite materialMaterials science
DOInot available

Abstract

fetched live from OpenAlex

The paper presents an overview of cases in which the analysis of the internal structure and mechanical properties of fibre reinforced composites is performed based on the micro-computed X-ray tomography (micro-CT) reconstruction of the composite reinforcement geometry. In all the cases, the analysis relies on structure tensor-based algorithms for quantification of the micro-CT image, implemented in VoxTex software.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.023
GPT teacher head0.261
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; a candidate call from one teacher head, 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of Twente Research InformationSame topicComposite Material MechanicsFrench-language works237,207