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Record W2460507574 · doi:10.1002/2016gl069179

Chemical stability of levoglucosan: An isotopic perspective

2016· article· en· W2460507574 on OpenAlexaff
Xuejing Sang, Iulia Gensch, Beatrix Kammer, Aftab Aslam Parwaz Khan, E. Kleist, W. Laumer, Patrick Schlag, Sebastian H. Schmitt, J. Wildt, Ran Zhao, Emma L. Mungall, Jonathan P. D. Abbatt, Astrid Kiendler‐Scharr

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLevoglucosanChemistryAerosolMass spectrometryParticulatesStable isotope ratioChemical stabilityAnalytical Chemistry (journal)FractionationEnvironmental chemistryChromatographyOrganic chemistryBiomass burning

Abstract

fetched live from OpenAlex

Abstract The chemical stability of levoglucosan was studied by exploring its isotopic fractionation during the oxidation by hydroxyl radicals. Aqueous solutions as well as mixed (NH 4 ) 2 SO 4 ‐levoglucosan particles were exposed to OH. In both cases, samples experiencing different extents of processing were isotopically analyzed by Thermal Desorption‐Gas Chromatography‐Isotope Ratio Mass Spectrometry (TD‐GC‐IRMS). From the dependence of levoglucosan δ 13 C and concentration on the reaction extent, the kinetic isotope effect (KIE) of the OH oxidation reactions was determined to be 1.00187±0.00027 and 1.00229±0.00018, respectively. Both show good agreement within the uncertainty range. For the heterogeneous oxidation of particulate levoglucosan by gas‐phase OH, a reaction rate constant of (2.67±0.03)·10 −12 cm 3 molecule −1 S −1 was derived. The laboratory kinetic data, together with isotopic source and ambient observations, give information on the extent of aerosol chemical processing in the atmosphere.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.041
GPT teacher head0.298
Teacher spread0.256 · 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
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

Citations39
Published2016
Admission routes1
Has abstractyes

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