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Record W2220004450 · doi:10.1002/2015gl066954

Size separation method for absorption characterization in brown carbon: Application to an aged biomass burning sample

2015· article· en· W2220004450 on OpenAlexafffund
Robert A. Di Lorenzo, Cora J. Young

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaNational Oceanic and Atmospheric Administration
KeywordsAbsorbanceSize-exclusion chromatographyAbsorption (acoustics)Mass spectrometryAerosolAnalytical Chemistry (journal)Electrospray ionizationElectrosprayChromatographyCarbon fibersChemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The majority of brown carbon (BrC) in atmospheric aerosols is derived from biomass burning (BB) and is primarily composed of extremely low volatility organic carbons. We use two chromatographic methods to compare the contribution of large and small light‐absorbing BrC components in aged BB aerosols with UV‐vis absorbance detection: (1) size exclusion chromatography (SEC) and (2) reverse phase high‐performance liquid chromatography. We observe no evidence of small molecule absorbers. Most BrC absorption arises from large molecular weight components (>1000 amu). This suggests that although small molecules may contribute to BrC absorption near the BB source, analyses of aerosol extracts should use methods selective to large molecular weight compounds because these species may be responsible for long‐term BrC absorption. Further characterization with electrospray ionization mass spectrometry (MS) coupled to SEC demonstrates an underestimation of the molecular size determined through MS as compared to SEC.

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)0.001
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 score0.902
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.052
GPT teacher head0.350
Teacher spread0.297 · 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

Citations81
Published2015
Admission routes2
Has abstractyes

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