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Ferrite Formation during Slow Continuous Cooling in Steel

2007· article· en· W2091975192 on OpenAlexaff
S.E. Offerman, Henrik Strandlund, N.H. van Dijk, Jilt Sietsma, E.M. Lauridsen, L. Margulies, Henning Friis Poulsen, John Ågren, Sybrand van der Zwaag

Bibliographic record

VenueMaterials science forum · 2007
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsRoyal Ottawa Mental Health Centre
FundersStichting voor de Technische WetenschappenDanmarks GrundforskningsfondEuropean Synchrotron Radiation Facility
KeywordsNucleationMaterials scienceFerrite (magnet)AusteniteBeta ferriteSynchrotronCarbon steelManganeseDiffractionMetallurgyCrystallographyThermodynamicsComposite materialMicrostructureChemistryCorrosion

Abstract

fetched live from OpenAlex

Ferrite formation during austenite decomposition in carbon-manganese steel is studied during slow continuous cooling by three-dimensional x-ray diffraction microscopy at a synchrotron source. The ferrite fraction and nucleation rate are measured simultaneously and independently in real time in the bulk of the specimen. Thermodynamic calculations involving both ortho- and paraequilibrium have been performed to determine the driving force for nucleation. From the experiments and thermodynamic calculations the activation energies are estimated for nucleation and the transfer of iron atoms across the interface of the cluster during ferrite nucleation in steel.

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)0.001
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 score0.003
Threshold uncertainty score0.383

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 communication0.0000.001
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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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