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Kinetic Transitions during Non-Partitioned Ferrite Growth in Fe-C-Mn Alloys

2011· article· en· W2050630796 on OpenAlex

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

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceAusteniteDecarburizationFerrite (magnet)Kinetic energyDiffusionManganeseMetallurgyThermodynamicsMicrostructureComposite materialPhysics

Abstract

fetched live from OpenAlex

Ferrite growth behavior in Fe-C-Mn alloys has been studied using controlled decarburization experiments. Two types of kinetic transition are considered. A first transition is proposed which involves a change from ParaEquibrium (PE) contact conditions at short times to Local-Equilibrium with Negligible Partitioning at longer times (LENP). This transition is attributed to the gradual build up of an alloying element spike due to the diffusion of Mn across the interface. The cross-interface mobility of Mn is estimated based on the experimental results. In some alloys, we observe a transition to extended PE states at high temperatures. A simple model which quantitatively describes the experimental observations over a range of composition and temperature is proposed. A key feature of this model is the introduction of an alloying element capacity of the moving ferrite/austenite interface, X*. The introduction of this quantity is purely guided by the experimental data and, at present, there is no physically based method for calculating it.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0020.002
Research integrity0.0000.001
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 head0.033
GPT teacher head0.244
Teacher spread0.211 · 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