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Record W2598114332 · doi:10.1029/2004gl019990

SO<sub>2</sub> depletion in tropospheric volcanic plumes

2004· article· en· W2598114332 on OpenAlexaff
A. J. S. McGonigle, Pierre Delmelle, Clive Oppenheimer, V. I. Tsanev, Thomas Delfosse, Glyn Williams‐Jones, Kyle G. Horton, Tamsin A. Mather

Bibliographic record

VenueGeophysical Research Letters · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPlumeVolcanoTroposphereAtmospheric sciencesEnvironmental sciencePanacheFlux (metallurgy)Relative humidityAerosolGeologyClimatologyMeteorology

Abstract

fetched live from OpenAlex

Ground based remote sensing techniques are used to measure volcanic SO2 fluxes in efforts to characterise volcanic activity. As these measurements are made several km from source there is the potential for in‐plume chemical transformation of SO2 to sulphate aerosol (conversion rates are dependent on meteorological conditions), complicating interpretation of observed SO2 flux trends. In contrast to anthropogenic plumes, SO2 lifetimes are poorly constrained for tropospheric volcanic plumes, where the few previous loss rate estimates vary widely (from ≪1 to >99% per hour). We report experiments conducted on the boundary layer plume of Masaya volcano, Nicaragua during the dry season. We found that SO2 fluxes showed negligible variation with plume age or diurnal variations in temperature, relative humidity and insolation, providing confirmation that remote SO2 flux measurements (typically of ≈500–2000 s old plumes) are reliable proxies for source emissions for ash free tropospheric plumes not emitted into cloud or fog.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

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)0.0000.000

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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

Citations86
Published2004
Admission routes1
Has abstractyes

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