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Record W2292918558 · doi:10.1144/sp437.2

Element flux to the environment of the passively degassing crater lake-hosting Kawah Ijen volcano, Indonesia, and implications for estimates of the global volcanic flux

2015· article· en· W2292918558 on OpenAlexaff
Vincent van Hinsberg, Nathalie Vigouroux, Stéphanie Palmer, Kim Berlo, Guillaume Mauri, Anthony E. Williams‐Jones, Jeffrey M. McKenzie, Glyn Williams‐Jones, Tobias P. Fischer

Bibliographic record

VenueGeological Society London Special Publications · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsSimon Fraser UniversityDouglas CollegeMcGill University
Fundersnot available
KeywordsImpact craterVolcanoGeologyCrater lakeFlux (metallurgy)GeochemistryPetrologyEarth scienceAstrobiology

Abstract

fetched live from OpenAlex

Abstract Volcanoes play an important role in the global cycling of elements by providing a pathway from the deep Earth to its surface. Here, we have constrained the flux to the environment for most elements of the periodic table for the passively degassing, crater lake-hosting Kawah Ijen volcano in the Indonesian arc. Our results indicate that emissions of Kawah Ijen are dominated by acid water outflow, especially for the ligands (Cl, F, Br), with active fumaroles contributing significant (semi)metals (e.g. Se, As, Sb, Hg), as well as C and S. The compositional signature of emissions from Kawah Ijen is similar to that of major volcanic emitters such as Etna, but element fluxes are smaller. This result provides the prerequisite foundation for extrapolating a small set of measured volcanic gas emissions to a global volcanic flux estimate. However, the aqueous flux (i.e. seepage of volcanic hydrothermal fluids and volcano-influenced groundwater) is at least as important in terms of element release, and the consideration of the gaseous flux alone thus represents a significant underestimate of the impact of volcanoes on their environment and the contribution of volcanic hydrothermal systems to global element cycling. Supplementary material: The full datasets of water and fumarole gas chemical analyses are available at https://doi.org/10.6084/m9.figshare.c.2134359

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)0.001
metaresearch head score (Gemma)0.001
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 score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.030
GPT teacher head0.234
Teacher spread0.203 · 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

Citations27
Published2015
Admission routes1
Has abstractyes

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