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Formation of Strain-induced Ferrite in Low Carbon Steels at Temperatures Above the Ae3

2013· article· en· W2081131139 on OpenAlexafffund
Vladimir V. Basabe, John J. Jonas, Chiradeep Ghosh

Bibliographic record

VenueISIJ International · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceElectron backscatter diffractionFerrite (magnet)NiobiumMicrostructureMetallurgyAusteniteCarbon steelCarbon fibersComposite material

Abstract

fetched live from OpenAlex

The formation of strain-induced ferrite was investigated in two low carbon steels and in a 0.036% Nb microalloyed low carbon steel at temperatures above the Ae3. Two distinct stages were observed, the first of which was characterized by the formation of Widmanstätten colonies with very fine plates of similar orientation. In the second stage, observed after further straining, the initial plates coalesced into polygonal ferrite grains. The transition from stage I to stage II was retarded by additions of carbon and niobium and slightly by an increase in strain rate. EBSD analysis revealed that the small misorientations (<1.5°) between Widmanstätten plates allow them to coalesce into grains. The 60° misorientations between some of the colonies suggest that they form from twinned regions of the parent austenite. A common characteristic of the polygonal grains is the presence of planar high angle boundaries, a feature inherited from the original Widmanstätten microstructure.

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 score0.006
Threshold uncertainty score0.011

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 head0.008
GPT teacher head0.200
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

Citations19
Published2013
Admission routes2
Has abstractyes

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