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Record W1610441103 · doi:10.1063/1.1711765

Magnetic Barkhausen Noise and Neutron Diffraction Techniques for the Study of Intergranular Residual Strains in Mild Steel

2004· article· en· W1610441103 on OpenAlexaff
Roxana Hutanu

Bibliographic record

VenueAIP conference proceedings · 2004
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceBarkhausen effectNeutron diffractionIntergranular corrosionResidual stressDiffractionUltimate tensile strengthComposite materialResidualWork (physics)MetallurgyMagnetic fieldMagnetizationMicrostructureOpticsMechanical engineeringComputer science

Abstract

fetched live from OpenAlex

Intergranular residual stresses (IS) are microscopic residual stresses which have been found to accumulate along the 〈100〉 direction in steels. The 〈100〉 direction is also the magnetic easy axis direction in steel. This work involved Magnetic Barkhausen Noise (MBN) studies on steel samples, deformed uniaxially to increasing levels of strain. The MBN results indicated that a bulk magnetic easy axis was produced by the deformation process, and neutron diffraction experiments showed that this easy axis was correlated with the tensile strain in grains oriented in the 〈100〉 direction.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.324

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 head0.026
GPT teacher head0.263
Teacher spread0.237 · 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 teacher head, 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

Citations0
Published2004
Admission routes1
Has abstractyes

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