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Record W2972923882 · doi:10.1016/j.epsl.2019.115783

Permeability evolution during non-isothermal compaction in volcanic conduits and tuffisite veins: Implications for pressure monitoring of volcanic edifices

2019· article· en· W2972923882 on OpenAlexafffund
S. Kolzenburg, Amy G. Ryan, James K. Russell

Bibliographic record

VenueEarth and Planetary Science Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersH2020 Marie Skłodowska-Curie ActionsNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsGeologyVolcanoCompactionElectrical conduitPermeability (electromagnetism)PetrologyOverpressureGeochemistrySeismologyGeomorphology

Abstract

fetched live from OpenAlex

Explosive volcanic eruptions are destructive geological phenomena that pose hazards of significant socioeconomic impact and potential loss of life. Effective risk mitigation and decision making prior to and during volcanic crises require real-time monitoring of gas overpressure – the single most important driving force for explosive eruptions. Development and release of gas overpressure are regulated by gas loss through permeable pathways that are inherently transient. Here, we use geometry-dependent conductive cooling models, in concert with the most up-to-date welding and permeability models, to assess the potential for "freezing in" permeability within (1) conduit-filling pyroclastic deposits and (2) tuffisite veins within the edifice. We find that both geometry and dimension of each deposit dictate its thermal evolution and, with that, its transient outgassing capacity. Rapid cooling of thin sheet-like tuffisite veins preserves high porosities and permeabilities. In contrast, wide cylindrical conduit-filling deposits cool slowly and permeability is annihilated over a period of minutes to hours. This highlights that conduit-filling deposits lose their outgassing capacity through welding, while tuffisite veins (previously thought to rapidly seal) can form long-lived outgassing features. We use the model results to calculate the time dependent gas flow partitioning between both degassing lithologies. Based on the reconstructed outgassing pattern we outline the potential to use the gas flow balance between the central conduit and distal fumaroles fed by tuffisite veins as a simple tool to monitor gas overpressure within a volcanic edifice.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.436

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 communication0.0000.001
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 head0.009
GPT teacher head0.199
Teacher spread0.190 · 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

Citations34
Published2019
Admission routes2
Has abstractyes

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