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Record W2008842790 · doi:10.1115/ipc2010-31659

Monitoring of Coating Disbondment by a Scanning Kelvin Probe Technique

2010· article· en· W2008842790 on OpenAlex
A.Q. Fu, Y. Frank Cheng

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venue2010 8th International Pipeline Conference, Volume 1 · 2010
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsKelvin probe force microscopeCoatingCorrosionVolta potentialMaterials scienceEvaporationMetallurgyElectrolyteAnalytical Chemistry (journal)Composite materialChemistryNanotechnologyAtomic force microscopyEnvironmental chemistryElectrodeThermodynamics

Abstract

fetched live from OpenAlex

The coating disbondment and corrosion of a X65 pipeline steel under coating were studied by scanning Kelvin probe (SKP) measurements. The effects of immersion time and wet-dry cycle on the Kelvin potential profile and the corrosion behavior of the steel were investigated. Kelvin potential measured on “intact” area is shifted negatively with time, indicating an increasing water uptake under the “intact” coating. There is a more negative Kelvin potential on disbonded area than that on “intact” area, which is attributed to corrosion reaction of steel occurring under the disbonded coating. During wet-dry cycle, the thickness of solution layer trapped under disbonded coating decreases due to evaporation of water, causing a negative shift of Kelvin potential. It is associated with the reduction of oxygen solubility in the concentrated solution during drying of electrolyte.

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)0.000
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 score0.105
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

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)0.0040.000

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 head0.280
Teacher spread0.260 · 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