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Record W2064213041 · doi:10.1002/elps.200700661

A practical interface for microfluidics and nanoelectrospray mass spectrometry

2008· article· en· W2064213041 on OpenAlexaff
Sergio L. S. Freire, Hao Yang, Aaron R. Wheeler

Bibliographic record

VenueElectrophoresis · 2008
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsParyleneMicrofluidicsAnalyteFabricationPhotolithographyPolymerMass spectrometryBiochipMaterials scienceInertNanotechnologyChromatographyChemistryAnalytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

We report a new method for fabricating nanospray ionization tips for MS, formed from glass substrates and the inert polymer, parylene-C. Using a single photolithography step, the emitters are formed contiguously with microchannels, such that no dead volumes are observed. In addition, because the devices are very thin (approximately 0.3 mm) and the tips are formed at rectangular corners, the Taylor cone volumes are small, which makes the method attractive for future integration with microfluidic separations. Device performance was demonstrated by evaluating diverse analytes, ranging from synthetic polymers, to peptides, to nucleic acids. For all analytes, performance was similar to that of conventional emitters (pulled-glass capillaries and the Agilent HPLC Chip) with the advantage of rapid, batch fabrication of identical devices.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.017
GPT teacher head0.286
Teacher spread0.268 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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