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Record W3014164473 · doi:10.5194/acpd-9-2533-2009

Secondary Organic Aerosol from biogenic VOCs over West Africa during AMMA

2009· article· en· W3014164473 on OpenAlexaff
G. Capes, J. G. Murphy, C. E. Reeves, James B. McQuaid, Jacqueline F. Hamilton, James R. Hopkins, Jonathan Crosier, P. I. Williams, Hugh Coe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersNatural Environment Research Council
KeywordsIsopreneAerosolSubtropicsEnvironmental scienceMonsoonAtmospheric sciencesClimatologyMeteorologyGeographyChemistryGeologyEcology

Abstract

fetched live from OpenAlex

Abstract. This paper presents measurements of organic aerosols above subtropical West Africa during the wet season using data from the UK Facility for Airborne Atmospheric Measurements (FAAM) aircraft. Measurements of biogenic volatile organic compounds (BVOC) at low altitudes over these subtropical forests were made during the African Monsoon Multidisciplinary Analysis (AMMA) field experiment during July and August 2006 mainly above Benin, Nigeria and Niger. Data from an Aerodyne Quadrupole Aerosol Mass Spectrometer show a median organic aerosol loading of 1.08 μg m−3 over tropical West Africa, which represents the first regionally averaged assessment of organic aerosol mass (OM) in this region during the wet season. This is in good agreement with predictions based on aerosol yields from isoprene and monoterpenes during chamber studies and model predictions based on partitioning schemes, contrasting markedly with the large under representations of OM in similar models when compared with data from mid latitudes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

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 studies0.0010.000
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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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 designObservational
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

Citations2
Published2009
Admission routes1
Has abstractyes

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