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Record W4415304838 · doi:10.30909/vol/gvni8317

Structural instability within the active crater of Poás volcano, Costa Rica

2025· article· en· W4415304838 on OpenAlexafffund
John Stix, Margaret Kalácska, J. Pablo Arroyo‐Mora, Oliver Lucanus, J. Maarten de Moor, Molly Urquhart, Carlos Campos-Vargas

Bibliographic record

VenueVolcanica · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Geology in Latin America and Caribbean
Canadian institutionsNational Research Council CanadaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsImpact craterVolcanoActive faultThermal infraredAerial imageryFault (geology)Series (stratigraphy)

Abstract

fetched live from OpenAlex

This study examines structural patterns in and around the crater of Poás volcano in Costa Rica to determine the current level of stability within the edifice. We used a series of Unoccupied Aerial Vehicle (UAV)-based photogrammetry and thermal infrared surveys to map the active crater, supplemented by satellite imagery to gain a broader view of the regional structural pattern near the volcano. We identified three areas within the eastern crater that exhibit various degrees of instability. The southern sector contains a possible explosion and/or collapse crater; the central zone shows evidence of structural disruption including collapse, fracturing, and/or faulting; and the northern sector contains a new explosion-collapse crater formed in April 2022. Through these three sectors, a principal north–south fault or series of faults truncates the eastern part of the active crater from the rest. These structural patterns continue north and south of the active edifice, demonstrating that east–west extension results in structural weakening at a variety of spatial scales. This weakening is enhanced by rock fracturing caused by volcanotectonic earthquakes and by hydrothermal alteration driven by high-temperature degassing. Because of its instability, the eastern crater area is deserving of further attention from a monitoring and forecasting perspective.

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 score0.604
Threshold uncertainty score0.769

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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