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Record W2969242667 · doi:10.5006/3319

Corrosion Evaluation of Ferritic Stainless Steels for Automotive Exhaust Applications

2019· article· en· W2969242667 on OpenAlexaff
Yoel Emun, Hatem S. Zurob, J.R. Kish

Bibliographic record

VenueCORROSION · 2019
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCorrosionMetallurgyMaterials scienceRust (programming language)Intergranular corrosionPolarization (electrochemistry)

Abstract

fetched live from OpenAlex

This study compares the localized (exterior) corrosion susceptibility of chromized steel to bench-mark ferritic stainless steels for automotive exhaust applications. Continuous near-neutral salt fog exposure (ASTM B117) was used for this purpose. Corrosion susceptibility was determined using mass loss measurements coupled with a post exposure metallographic examination. Complementary potentiodynamic polarization measurements were made in the bulk salt solution to help interpret the relative performance. The elevated Cr content provided by the chromizing surface treatment provides comparable corrosion resistance to the more highly alloyed ferritic stainless steels studied. The major factor affecting localized corrosion susceptibility is the formation of rust deposits, which act as effective pit-like corrosion initiation sites.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.039
GPT teacher head0.329
Teacher spread0.290 · 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 designObservational
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

Citations6
Published2019
Admission routes1
Has abstractyes

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Same venueCORROSIONSame topicHydrogen embrittlement and corrosion behaviors in metalsFrench-language works237,207