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On Parameters Related to Continuous and Discontinuous Recrystallization and Subsequent Grain Growth

2000· article· en· W2071951285 on OpenAlexaff
Hai Ou Jin, Jian Li, Fumie Seki, S. Saimoto

Bibliographic record

VenueMaterials science forum · 2000
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsQueen's UniversityNovelis (Canada)
Fundersnot available
KeywordsMaterials scienceRecrystallization (geology)SwagingDynamic recrystallizationCrystalliteMetallurgyGrain sizeGrain growthGrain boundary strengtheningGrain boundaryAluminiumHot workingMicrostructureGeology

Abstract

fetched live from OpenAlex

Ultra-fine grain structure of less than 5 μm grain size in aluminum and aluminum alloys can be obtained by continuous recrystallization and dynamic recrystallization under different types of deformation such as compression, swaging and cold rolling. The occurrence of continuous recrystallization and dynamic recrystallization is determined by various parameters, mainly by the solute Fe level in the aluminum matrix, but also by the initial grain size, the local strain state, the specific orientation of each individual crystallite and the mis-orientation at the grain boundaries. The subsequent grain growth is greatly affected by these parameters as well as the equilibrium and non-equilibrium segregation of Fe solute to the newly formed grain boundaries, and the interaction of precipitate particles with the migrating grain or subgrain boundaries.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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 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

Citations3
Published2000
Admission routes1
Has abstractyes

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