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Record W4236810371 · doi:10.1063/1.5023288.1

10.1063/1.5023288.1

2018· dataset· en· W4236810371 on OpenAlexaff

Bibliographic record

VenueDefault Digital Object Group · 2018
Typedataset
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsCanadian Light Source (Canada)Norcada (Canada)McMaster University
Fundersnot available
KeywordsElectrodeStripping (fiber)MicrofabricationCopperElectrolyteMaterials scienceElectrochemistrySiliconDeposition (geology)Absorption (acoustics)Etching (microfabrication)NanotechnologyAnalytical Chemistry (journal)Chemical engineeringMetallurgyChemistryComposite materialLayer (electronics)Physical chemistry

Abstract

fetched live from OpenAlex

We report the design and performance of a 3-electrode device for real time in situ scanning transmission X-ray microscopy studies of electrochemical processes under both static (sealed, non-flow) conditions and with a continuous flow of electrolytes. The device was made using a combination of silicon microfabrication and 3D printing technologies. The performance is illustrated by results of a study of copper deposition and stripping at a gold working electrode. X-ray absorption spectromicroscopy at the Cu 2p edge was used to follow the evolution as a function of potential and time of the spatial distributions of Cu(0) and Cu(i) species electro-deposited from an aqueous solution of copper sulphate. The results are interpreted in terms of competing mechanisms for the reduction of Cu(ii).

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.672
Threshold uncertainty score0.958

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.008
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.3280.561

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2018
Admission routes1
Has abstractyes

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