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Record W2058042369 · doi:10.1063/1.2767638

Quantifying cation grain boundary diffusion

2007· article· en· W2058042369 on OpenAlexafffund
John A. Nychka, D.R. Clarke, J.R. Dryden

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsGrain boundaryMaterials scienceGroove (engineering)Grain boundary diffusion coefficientOxideDiffusionAluminum oxideFlux (metallurgy)AluminiumSurface diffusionMetallurgyChemical physicsChemistryThermodynamicsMicrostructurePhysical chemistry

Abstract

fetched live from OpenAlex

Evolution in the shape of grooves formed at grain boundaries at the air/aluminum oxide interface is analyzed for the case in which there is both diffusion along the oxide surface and oxidation-induced mass flow along grain boundaries of the already-formed oxide. The shape evolution is compared with atomic force microscope measurements of the groove profiles produced when thermally grown alumina on FeCrAl alloys is polished flat and reoxidized. A method of quantifying the grain boundary flux, based upon the shape of the surface profile, is presented.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.461

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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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

Citations3
Published2007
Admission routes2
Has abstractyes

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