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Record W4382133716 · doi:10.1007/s11085-023-10163-5

Evaluating Wagner Oxidation Criteria for Protective Al2O3 Scale Formation in Ni-Based Superalloys

2023· article· en· W4382133716 on OpenAlexfundno aff
J. W. X. Wo, Mark Hardy, H.J. Stone

Bibliographic record

VenueHigh Temperature Corrosion of Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCambridge Trust
KeywordsSuperalloyMaterials scienceMetallurgyOxideVolume fractionAlloyComposite material

Abstract

fetched live from OpenAlex

Abstract An assessment is made of the Wagner transition criteria for predicting the formation of a continuous Al2O3scale in Ni-based superalloys. Predictions are compared with data from an experimental Ni-based superalloy as well as commercial superalloys for which published data are available. The methodology was generally successful in predicting the transition temperature of the commercial superalloys but underpredicted the transition temperature of the experimental superalloy by approximately 50–100 °C. The difference in the transition temperature of the experimental superalloy to form a continuous Al2O3scale is primarily attributed to a complex oxide subscale that increased the internal volume fraction of oxide and led to reduced oxygen ingress. The sensitivity and limitations of the methodology are discussed, and recommendations are made to refine the methodology to facilitate the interpretation of oxidation behaviour in polycrystalline Ni-based superalloys.

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)0.001
metaresearch head score (Gemma)0.003
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
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.031
GPT teacher head0.309
Teacher spread0.277 · 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

Citations27
Published2023
Admission routes1
Has abstractyes

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