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Record W4360616615 · doi:10.1002/maco.202213705

Effect of alloying elements on aqueous corrosion of nickel‐based alloys at high temperatures: A review

2023· review· en· W4360616615 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

VenueMaterials and Corrosion · 2023
Typereview
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsWestern University
Fundersnot available
KeywordsCorrosionMetallurgyMaterials scienceNickelOxidePassivityAlloyMolybdenumTungstenEngineering

Abstract

fetched live from OpenAlex

Abstract Nickel‐based alloys are well‐known multicomponent alloys with a composition carefully balanced to provide the desired properties for various industrial applications. While these alloys are corrosion resistant, under severe conditions corrosion can still occur, which can result in serious damage to a system in operation. To improve their reliability, the composition of nickel‐based alloys can be tailored to particular operating conditions. To improve their corrosion resistance, alloying elements such as chromium, molybdenum (+tungsten), and copper can be added, which promote the oxide formation process and thereby contribute to oxide passivity. This paper reviews and draws conclusions from existing literature on nickel‐based alloy corrosion and oxide formation in high‐temperature environments.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
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 head0.020
GPT teacher head0.296
Teacher spread0.276 · 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