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Record W1968219763 · doi:10.1021/ac2030128

Negative Chemical Ionization GC/MS Determination of Nitrite and Nitrate in Seawater Using Exact Matching Double Spike Isotope Dilution and Derivatization with Triethyloxonium Tetrafluoroborate

2012· article· en· W1968219763 on OpenAlexaff
Enea Pagliano, Juris Meija, Ralph E. Sturgeon, Zoltán Mester, Alessandro D’Ulivo

Bibliographic record

VenueAnalytical Chemistry · 2012
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsChemistryChemical ionizationDerivatizationNitriteNitrateChromatographyIsotope dilutionGas chromatographyMass spectrometryGas chromatography–mass spectrometryDetection limitIonizationOrganic chemistry

Abstract

fetched live from OpenAlex

The alkylation of nitrite and nitrate by triethyloxonium tetrafluoroborate allows determination of their ethyl esters by headspace gas chromatography/mass spectrometry (GC/MS). In the present study, significant improvement in analytical performance is achieved using negative chemical ionization providing detection limits of 150 ng/L for NO(2)(-) and 600 ng/L for NO(3)(-), an order of magnitude better than those achieved using electron impact ionization. The derivatization procedure was optimized and alkaline conditions adopted to minimize conversion of nitrite to nitrate (determined to be 0.07% at 100 mg/L NO(2)(-)) and to avoid the exchange of oxygen between the analytes and the solvent (water). Quantitation entails use of isotopically enriched standards (N(18)O(2)(-) and (15)NO(3)(-)), which also permits monitoring of potential conversion from nitrite to nitrate during the analysis (double spike isotope dilution).

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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 designBench or experimental
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

Citations40
Published2012
Admission routes1
Has abstractyes

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