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Record W4416767083 · doi:10.1186/s13617-025-00155-2

Diffuse soil gas emission measurements on the volcanic island of Saba, Lesser Antilles

2025· article· en· W4416767083 on OpenAlexafffund
Florentine C. Zwillich, Kim Berlo, Elske van Dalfsen, Daniele L. Pinti

Bibliographic record

VenueJournal of Applied Volcanology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversité du Québec à MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransectVolcanoFlux (metallurgy)Soil gasIsotopes of carbonSoil waterStable isotope ratioSpatial variabilityMethane

Abstract

fetched live from OpenAlex

Abstract Monitoring changes of geochemical parameters in the subsurface around volcanoes is crucial for hazard assessment and early warning. This study establishes a baseline of soil CO $$_2$$ emission from its flanks of the Mount Scenery stratovolcano, on Saba in the Caribbean Netherlands, during its period of quiescence. The soil CO $$_2$$ flux and carbon isotope variation were mapped across the island to find patterns and locations of higher flux. Additionally, soil gas was analyzed for helium isotopes at ‘Green Gut’, a location which has an anomalous soil temperature. Results reveal spatial variations in temperature and soil CO $$_2$$ fluxes across the island, with higher temperature and fluxes observed along a transect from the southwest to the island’s north side. The anomalous sites identified from soil CO $$_2$$ flux and carbon isotopes measurements align with known alteration and temperature anomalies, including an abandoned mine in The Bottom and cracks along the road in ‘Green Gut’. The identified transect partially overlaps with a previously proposed ancient sector collapse, but our results suggest an extension northward. Integrated soil CO $$_2$$ flux and carbon isotope data across the island indicate that the emitted gas is a mixture of biogenic, atmospheric, and hydrothermal-magmatic sources.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

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 head0.016
GPT teacher head0.214
Teacher spread0.198 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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