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Record W4200151506 · doi:10.37775/eis.2021.2.3

Review: Deformed and recrystallized structures in FCC materials

2021· article· en· W4200151506 on OpenAlexaff
Purnima Chakravarty, Jurij J. Sidor

Bibliographic record

VenueMérnöki és Informatikai Megoldások · 2021
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsSavaria (Canada)
Fundersnot available
KeywordsRecrystallization (geology)Materials scienceDynamic recrystallizationHot workingMetallurgyMicrostructureGeology

Abstract

fetched live from OpenAlex

The evolution in the field of recrystallization related studies in FCC metals is summarized in this paper. The process of recrystallization which is initiated by stored energy is provided by dislocations. However, dislocations are introduced during the process of deformation, hence both aspects are covered, as well as the kinetics of recrystallization is well elaborated. The key features of recrystallization: role of misorientations; deformation and recrystallization textures; are described and most importantly recent issues on recrystallization of FCC metals are documented in this paper. The final remarks contain the future aspects of studies in the field of recrystallization of materials with FCC crystal structure.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2021
Admission routes1
Has abstractyes

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