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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 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

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.054
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0020.000

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