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Record W3025744123 · doi:10.1149/09707.0523ecst

Electropolishing of Inside Surfaces of Stainless Steel Tubing

2020· article· en· W3025744123 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

VenueECS Transactions · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Machining and Optimization Techniques
Canadian institutionsÉcole de Technologie SupérieureConcordia University
Fundersnot available
KeywordsElectropolishingMaterials scienceSurface roughnessSurface finishElectrodeBrightnessEccentricity (behavior)Tube (container)MetallurgyComposite materialOpticsChemistryPhysics

Abstract

fetched live from OpenAlex

This study aims to investigate the electropolishing of inside walls of stainless steel 316 tubing using internal counter-electrodes with a focus on the effect of parameters such as interelectrode-gap, length, and the outer diameter of the tubing, and the counter-electrode eccentricity on the final roughness and brightness of the surface. It was observed that under the proper combination of electropolishing voltage and duration, irrespective of the initial surface condition of the samples, they were all significantly brightened, and their surface roughness was decreased to almost similar final values. The results indicated that the interelectrode-gap had a rather low impact on the final roughness of the surface but strongly affected its final brightness. It was also concluded that during the electropolishing process, the hydrodynamic conditions inside the tube could significantly affect the surface quality.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.306

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)0.0000.000

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 head0.220
Teacher spread0.209 · 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