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An enhanced microfluidic chip coupled to an electrospray Qstar mass spectrometer for protein identification

2000· article· en· W2008842530 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

VenueElectrophoresis · 2000
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsAlberta EnergyNational Research Council Canada
Fundersnot available
KeywordsMicrofluidicsElectrosprayInterfacingMass spectrometryBiomoleculeChromatographyChemistryFluidicsAnalyteNanotechnologyMaterials scienceAnalytical Chemistry (journal)Computer scienceComputer hardware

Abstract

fetched live from OpenAlex

The combination of microfabricated fluidic systems (muFAB) and electrospray mass spectrometers (ESI-MS) will provide multiplexed and integrated analytical systems for proteins and other biomolecules. Implementation of this novel approach requires the development of robust and user-friendly muFAB devices. Here, we present new approaches that improve the robustness, user friendliness and performance of muFAB devices coupled to MS. First, we present the development of a convenient mount to connect a muFAB device to the ESI-MS and the incorporation of filters in the reservoirs and exit of the muFAB. This mount facilitates interfacing and significantly reduces the chemical noise observed by the MS. Furthermore, we demonstrate improvements in sample handling and delivery by using either a nonaqueous electrolyte or a cationic coating on the surfaces in the muFAB device and transfer capillary. These improvements are applied to protein analysis by continuous infusion of proteolytic digests.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.096
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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