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Record W1981491574 · doi:10.1002/srin.201200226

Formation of Widmanstätten Ferrite in a 0.036% Nb Low Carbon Steel at Temperatures Above the Ae<sub>3</sub>

2013· article· en· W1981491574 on OpenAlexafffund
Vladimir V. Basabe, John J. Jonas, Chiradeep Ghosh

Bibliographic record

Venuesteel research international · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFerrite (magnet)Materials scienceElectron backscatter diffractionMicrostructureScanning electron microscopeOptical microscopeCoalescence (physics)Carbon steelMetallurgyDiffractionElectron microscopeComposite materialOpticsCorrosionPhysics

Abstract

fetched live from OpenAlex

The formation of Widmanstätten ferrite was investigated in a 0.036% Nb microalloyed steel at temperatures above the Ae3 using optical microscopy, scanning electron microscopy, and electron backscatter diffraction. Such strain‐induced ferrite appears to form in two consecutives stages: (i) stage I, first observed at strains below 0.5, leads to the presence of Widmanstätten ferrite plates only about 200 nm wide, (ii) stage II, observed at strains >0.5, involves the coalescence of the Widmanstätten plates into grains. Thus the microstructures formed by dynamic transformation are composed of fresh Widmanstätten plates (stage 1) and polygonal grains (stage 2). Over the experimental temperature range of 836–896°C, the ultrafine ferrite plates and grains have areas below 2 µm2 and are difficult to detect using optical microscopy.

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 score0.005
Threshold uncertainty score0.009

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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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

Citations32
Published2013
Admission routes2
Has abstractyes

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