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Record W1973106802 · doi:10.5006/1.3381566

Nominally Anaerobic Corrosion of Carbon Steel in Near-Neutral pH Saline Environments

2010· article· en· W1973106802 on OpenAlexaff
Brent W.A. Sherar, Peter Keech, Z. Qin, Fraser King, David W. Shoesmith

Bibliographic record

VenueCORROSION · 2010
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsVancouver Island UniversityWestern University
Fundersnot available
KeywordsCorrosionCarbon steelAnaerobic exerciseMetallurgyMaterials scienceAnaerobic corrosionSalineCarbon fibersComposite materialComposite number

Abstract

fetched live from OpenAlex

Gas transmission pipeline corrosion commences when coatings disbond, exposing the steel to groundwater. When this occurs, a number of anaerobic and aerobic corrosion scenarios can be envisaged. The initial nominally anaerobic corrosion period has been investigated by applying a combination of electrochemical methods (i.e., corrosion potential, linear polarization resistance, and electrochemical impedance spectroscopy [EIS] measurements) and surface analytical techniques (scanning electron microscopy, energy-dispersive x-ray spectroscopy, and Raman spectroscopy). An evolution in film properties was observed and attributed to the entry of adventitious oxygen into faults within the preformed film. This leads to an increase in overall corrosion and a change in properties of the film as detected by EIS and Raman analysis. This article describes the mechanism involved in this transition, and provides a basis for a more extensive study of the corrosion process encountered on switching between anaerobic and aerobic conditions. The overall goal of this study was to provide a mechanistic basis for the corrosion scenarios possible on gas transmission pipelines.

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)0.001
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
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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

Citations31
Published2010
Admission routes1
Has abstractyes

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Same venueCORROSIONSame topicCorrosion Behavior and InhibitionFrench-language works237,207