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Record W1995963857 · doi:10.1063/1.4865759

Note: Benign and reproducible preparation of titanium tips

2014· article· en· W1995963857 on OpenAlexaff
Asaduzzaman Mohammad, Zachary Arnott, Y. Wang, Peter Kruse

Bibliographic record

VenueReview of Scientific Instruments · 2014
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElectropolishingEthylene glycolMaterials scienceEtching (microfabrication)ElectrolyteFabricationTitaniumElectrochemistryEthylene oxideChemical engineeringOxideLayer (electronics)NanotechnologyComposite materialMetallurgyElectrodeChemistry

Abstract

fetched live from OpenAlex

Fabrication of titanium tips via electrochemical etching is commonly hindered by the formation of a tough oxide layer. A new one-step approach based on dc etching in a non-aqueous electrolyte is presented. The electrochemical tip etching was carried out at 20 V in a benign etchant of 1M NaCl in ethylene glycol. Tip radii below 100 nm are demonstrated using current cut-off control and approaching 150 nm without cut-off control. The simplicity and efficiency of the approach eliminates pre and post electropolishing steps due to the electropolishing capability of a NaCl-ethylene glycol based 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.

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)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.009

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 head0.013
GPT teacher head0.280
Teacher spread0.267 · 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
GenreMethods

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

Citations2
Published2014
Admission routes1
Has abstractyes

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