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Record W2052507142 · doi:10.1002/elps.200500889

Peak identification in capillary isoelectric focusing using the concept of relative peak position as determined by two isoelectric point markers

2006· article· en· W2052507142 on OpenAlexaff
Jiaqi Wu, Tiemin Huang

Bibliographic record

VenueElectrophoresis · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsConvergent Manufacturing Technologies (Canada)
Fundersnot available
KeywordsIsoelectric focusingChemistryIsoelectric pointAnalytical Chemistry (journal)ChromatographySample (material)PiPosition (finance)LinearityCapillary actionPhysicsThermodynamics

Abstract

fetched live from OpenAlex

In CIEF analysis, sample peaks can be identified by their relative peak positions (RPP) that are determined using only two internal pI markers. The two internal pI marker peaks should bracket, as close as possible, the sample peaks. The RPP values of the sample peaks are then calculated using the pI values, peak positions of the two pI markers, and peak position of the sample. Use of this method can effectively compensate for pH gradient distortions that often occur as a result of salts. Also, as shown by the results of this paper, regardless of the linearity of the pH gradient established by the given carrier ampholytes, sample peaks can be identified within an SD of 0.1 pH unit in RPP (<2% RSD) as long as the sample is run using the same carrier ampholytes and maintaining salt concentrations in the range of 0-15 mM.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.002

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 head0.003
GPT teacher head0.205
Teacher spread0.202 · 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

Citations36
Published2006
Admission routes1
Has abstractyes

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