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Record W2998622065 · doi:10.1080/02670836.2019.1706816

Microstructure and texture evolution during annealing of Ti–6Al–4V alloy

2020· article· en· W2998622065 on OpenAlexaff
Malaya Kumar Debta, B. Bishoyi, R.K. Sabat, Waqas Muhammad, Santosh K. Sahoo

Bibliographic record

VenueMaterials Science and Technology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicTitanium Alloys Microstructure and Properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAnnealing (glass)Materials scienceMicrostructureAlloyMetallurgyGrain boundaryGrain growth

Abstract

fetched live from OpenAlex

Ti–6Al–4V plates were subjected to warm rolling at 600°C up to 85% reduction in thickness followed by annealing at 850°C for different soak periods. It was observed that the ‘β’ grains were prevalent along the grain boundaries and at the triple junctions of ‘α’ grains. The samples were found to be fully recrystallised after 30 min of annealing time. Further, globularizarion of ‘α’ grains was observed during the progress of annealing. The recrystallisation mechanism was identified to be through sub-grain formation and its growth. A dominant near basal texture, i.e. , was observed in the samples after annealing.

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 score0.004
Threshold uncertainty score0.008

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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