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Record W2102743809 · doi:10.1093/jat/31.6.342

Quantitative Endogenous Formate Analysis in Plasma Using Headspace Gas Chromatography Without a Headspace Analyzer

2007· article· en· W2102743809 on OpenAlexaff
AbdulRazaq Sokoro, Denis C. Lehotay, J. Eichhorst, R. G. Treble

Bibliographic record

VenueJournal of Analytical Toxicology · 2007
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsUniversity of ReginaSaskatchewan Disease Control Laboratory
Fundersnot available
KeywordsChromatographyChemistryFormic acidGas chromatographyDetection limitElutionFlame ionization detectorQuantitative analysis (chemistry)FormateEthanolAnalytical Chemistry (journal)CatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

The objective was to develop a simple routine method for quantitative measurement of endogenous formic acid in plasma and whole blood using headspace gas chromatography-flame ionization detection. (GC-FID). Two-hundred microliters of sample was placed in a 1-mL glass vial. Fifty microliters of aqueous ethanol (10%) was added as an internal standard and a derivatizing agent. Ethylformate formation was enhanced by addition of 200 microL concentrated sulfuric acid as a catalyst. The vials were then sealed immediately and placed in a water bath for 15 min at 60 degrees C. One milliliter of this headspace gas was siphoned using a gas-tight syringe and injected into a GC-FID fitted with a capillary column. Ethanol eluted at approximately 3.0 min, and ethylformate eluted around 4.7 min. The limit of quantitation for ethylformate was 0.026 mmol/L, and the limit of detection was 0.020 mmol/L. Imprecisions for spiked plasma samples at 0.25 and 1 mmol/L were 10% and 9%, respectively and recoveries were at 100% and 108%, respectively. A simple, reliable, and highly specific headspace analysis method for quantifying endogenous formate without the use of a headspace analyzer was developed. This method enables the routine clinical analysis of formate in plasma and whole blood samples.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.372
Teacher spread0.309 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2007
Admission routes1
Has abstractyes

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