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The Effect of Intercritical Deformation on Microstructure Development in Thermomechanically-Processed Low-Silicon TRIP-Assisted Steels

2013· article· en· W2091744857 on OpenAlex
Seyed Mohammad Kazem Hosseini, A. Zarei‐Hanzaki, Stephen Yue

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.

Bibliographic record

VenueAdvanced materials research · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceAusteniteMicrostructureMetallurgyVolume fractionBainiteFerrite (magnet)Thermomechanical processingDeformation (meteorology)SiliconTRIP steelOptical microscopeScanning electron microscopeComposite material

Abstract

fetched live from OpenAlex

The effect of intercritical deformation on development of microstructure in low-silicon contents multiphase TRIP-assisted steels were investigated by laboratory simulation of controlled-thermomechanical processing in an automated hot compression testing machine. A typical multiple cooling stages TMP program was applied and samples were deformed in intercritical region to different strains. Microstructures of samples were characterized by optical and scanning electron microscopy, XRD and Mössbauer. The result indicated that intercritical straining increases volume fraction of polygonal ferrite and granular-type retained austenite particles, but reduces fraction of bainite. The increase in retained austenite volume fraction is attributed to strain-assisted diffusion of carbon and to refinement of retained austenite particles.

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)0.001
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 score0.047
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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