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Record W4200034146 · doi:10.3389/fchem.2021.756745

Vitamin E Acetate Determination in Vaping Liquids and Non-targeted Analysis of Vaping Emissions of Diluents of Concern, Vitamin E Acetate and Medium-Chain Triglycerides Oil

2021· article· en· W4200034146 on OpenAlexafffund
Ivana Kosarac, Cariton Kubwabo, Guru Prasad Katuri, Dora Petraccone, T. Mischki

Bibliographic record

VenueFrontiers in Chemistry · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsHealth Canada
FundersHealth CanadaGovernment of Canada
KeywordsChromatographyChemistryDetection limitDiluentNicotineGas chromatography–mass spectrometryGas chromatographyAnalyteVitaminMass spectrometryVitamin EFood scienceBiochemistryOrganic chemistryMedicineAntioxidant

Abstract

fetched live from OpenAlex

During the summer of 2019, cases of lung injury associated with vaping emerged in North America, including among individuals who reported exclusive use of nicotine vaping liquids. Once vitamin E acetate was identified as a potential causative agent a quantitative method based on a simple sample dilution, separation by gas chromatography and analysis by triple quadrupole mass spectrometry (GC MSMS) was developed. Method detection limit (MDL) and limit of quantification (LOQ) were determined at 0.159 µg/mL and 0.505 µg/mL, respectively. The analysis was performed on a subset of 203 commercially sourced nicotine containing vaping liquids of various flavour profile and nicotine range (nicotine free-59 mg/mL) from an internal inventory. The target analyte, Vitamin E Acetate, was not detected in any samples analyzed, as expected, given the reported detection in literature and high association of the chemical with cannabis and not nicotine containing vaping products.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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