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Record W2537024640 · doi:10.1051/matecconf/20168006004

Modeling Metadynamic Recrystallization of a Die Steel during Ingot Breakdown Process

2016· article· en· W2537024640 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMATEC Web of Conferences · 2016
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIngotMaterials scienceIsothermal processRecrystallization (geology)MetallurgyForgingCompression (physics)Deformation (meteorology)Compression testDynamic recrystallizationComposite materialStructural engineeringMicrostructureThermodynamicsHot workingEngineeringAlloyGeology

Abstract

fetched live from OpenAlex

Ingot forging processes often consist of several successive deformation steps with high interpass times, during which metadynamic recrystallization (MDRX) occurs. Two-stage isothermal compression tests were carried out at 1150°C and 1200°C with strain rates of 0.25-2s−1 and interpass times of 5-25s. Based on the experimental results, a material model for MDRX is proposed. The constitutive model was implemented in Forge NxT 1.1® software to simulate the multistage compression. Results from the material model are consistent with the numerical analysis and experimental results.

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.

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 score0.246
Threshold uncertainty score0.332

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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