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External Reference Samples for Residual Stress Analysis by X-Ray Diffraction

2014· article· en· W2109374838 on OpenAlexaff
Fabien Lefèbvre, Eric Wasniewski, Manuel François, J. Cacot, P. Le-Bec, E. Baumhauer, Denis Bouscaud, Thierry Bergey, D. Blaize, David Gloaguen, A. Cosson, Sébastien Jégou, Yann Cheynet, S. Leray, M. Meheux, J.C. Monvoisin, Patrick Allain, Juan C. Vidal, Jean‐Michel Sprauel, P. Goudeau, C. Charles, L. Daflon, Claas Fischer, L. Desmas, A. Ouâkka, Marie-José Moya, Y. Bordiec, Hédi Hamdi

Bibliographic record

VenueAdvanced materials research · 2014
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsDiffractionResidual stressCalibrationResidualMaterials scienceX-rayX-ray crystallographySample (material)Computer sciencePhysicsMathematicsOpticsStatisticsMetallurgyAlgorithm

Abstract

fetched live from OpenAlex

The GFAC (French Association for residual stress analysis) has been working for several years on external reference samples in relation with the EN 15305-2009 standard. The purpose of this campaign is to provide an external reference sample to each laboratory involved in the round-robin to allow a good calibration, a good quality control of their X-ray diffraction system and an easiest way to compare results between laboratories. All the procedures to qualify external reference materials will be described in the paper.

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)0.004
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.022
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0220.010

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 head0.048
GPT teacher head0.355
Teacher spread0.307 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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