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Record W2081949462 · doi:10.1029/2002jd002883

Concentration and stable carbon isotopic composition of ethane and benzene using a global three‐dimensional isotope inclusive chemical tracer model

2003· article· en· W2081949462 on OpenAlexafffund
Alexandra E. Thompson, J. Rudolph, Franz Röhrer, Olaf Stein

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Association of University Women
KeywordsBenzeneTRACERAtmospheric chemistryCarbon fibersIsotopes of carbonStable isotope ratioIsotopeFractionationAtmosphere (unit)Mass-independent fractionationIsotope fractionationChemistryEnvironmental chemistryKinetic isotope effectMaterials scienceMeteorologyDeuteriumOzoneTotal organic carbonOrganic chemistryPhysicsNuclear physics

Abstract

fetched live from OpenAlex

A three‐dimensional global chemical tracer model of the atmosphere has been adapted to include the stable carbon isotopic composition and isotopic fractionation of ethane and benzene. For computational efficiency the chemistry was based on a prescribed OH‐radical concentration field, and therefore the feedback of ethane and benzene chemistry on the atmospheric OH‐radical concentrations was not considered. The Emission Database for Global Atmospheric Research (EDGAR) V2.0 emission database used needed to be scaled by a factor of 2.22 in order to have good agreement between observed and modeled concentrations. Modeled isotopic compositions were consistent with the few published observations. The global distribution of modeled stable carbon isotope ratios and the derived mean photochemical ages of ethane and benzene are presented. The model predicts distinct regimes of photochemical aging and air mass mixing for polar regions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.295
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations24
Published2003
Admission routes2
Has abstractyes

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