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Record W2047032757 · doi:10.5194/amt-8-2301-2015

A method for stable carbon isotope ratio and concentration measurements of ambient aromatic hydrocarbons

2015· article· en· W2047032757 on OpenAlexafffundabout
A. Kornilova, S. Moukhtar, M. Saccon, Lin Huang, W. Zhang, J. Rudolph

Bibliographic record

VenueAtmospheric measurement techniques · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change CanadaYork University
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric Sciences
KeywordsCartridgeIsotope-ratio mass spectrometryChemistryEnvironmental chemistryThermal desorptionIsotopes of carbonCarbon fibersIsotope analysisAdsorptionGas chromatographyIsotopeMass spectrometryCombustionDesorptionAnalytical Chemistry (journal)Total organic carbonChromatographyOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Abstract. A technique for compound-specific analysis of stable carbon isotope ratios and concentration of ambient volatile organic compounds (VOCs) is presented. It is based on selective VOC sampling onto adsorbent-filled cartridges by passing large volumes of air (up to 80 L) through the cartridge. The hydrocarbons are recovered by thermal desorption followed by two-step cryogenic trapping and then are separated by gas chromatography in the laboratory. Once separated, individual VOCs are subjected to online oxidation in a combustion interface and isotope ratio analysis by isotope ratio mass spectrometry. The method allows measurements of stable carbon isotope ratios of ambient aromatic VOCs present in low pptV to ppbV levels with an accuracy of typically better than 0.5 ‰. The precision of concentration measurements is better than 10%. Examples of measurements conducted as part of a joint Environment Canada–York University (EC-YU) measurement campaign at a semi-rural location demonstrate that the ability to make accurate measurements in air with low VOC mixing ratios is important to avoid bias from an overrepresentation of samples that are strongly impacted by recent emissions.

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)0.002
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 score0.445
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.055
GPT teacher head0.260
Teacher spread0.206 · 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

Citations10
Published2015
Admission routes3
Has abstractyes

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