MétaCan
Menu
Back to cohort
Record W2034900511 · doi:10.2320/matertrans.42.2050

Cube Texture Development in an Al-Mg-Mn Alloy Sheet Worked by Continuous Cyclic Bending

2001· article· en· W2034900511 on OpenAlexaff
Yoshimasa Takayama, Jerzy nbsp A. Szpunar, Hyo-Tae Jeong

Bibliographic record

VenueMATERIALS TRANSACTIONS · 2001
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceAnnealing (glass)Electron backscatter diffractionAlloyMetallurgySurface layerSurface finishComposite materialLayer (electronics)Microstructure

Abstract

fetched live from OpenAlex

Changes in texture after the continuous cyclic bending (CCB) and the subsequent annealing in sheets of an Al–4.7 mass%Mg–0.7 mass%Mn alloy have been investigated. The CCB was recently proposed as a straining technique that generates a high strain on the surface and a much lower strain in the central layer of the sheet. The Cube texture in the surface layer is sharpened remarkably during the CCB process and the annealing that follows. The 50 CCB passes lead to a sharper texture in all layers of the sheet. After annealing, marked development of the Cube component is observed in the surface layer. On the other hand, for the 20 pass-CCBent sample, the Cube texture appears only after annealing in a salt bath, while this texture is not observed after annealing both in Ar and in air. The mechanism of texture formation and the effect of processing on the sharpening of Cube texture is discussed based on results obtained from the electron backscatter diffraction pattern (EBSP) analysis and from the in-situ measurement of X-ray peak intensity during heating.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.244
Teacher spread0.233 · 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

Citations18
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueMATERIALS TRANSACTIONSSame topicMetal Forming Simulation TechniquesFrench-language works237,207