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Record W1525270929 · doi:10.1002/grl.50176

The effect of pre‐existing craters on the initial development of explosive volcanic eruptions: An experimental investigation

2013· article· en· W1525270929 on OpenAlexafffund
Jacopo Taddeucci, Greg A. Valentine, Ingo Sonder, James D. L. White, Pierre‐Simon Ross, Piergiorgio Scarlato

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaUniversity at BuffaloIstituto Nazionale di Geofisica e Vulcanologia
KeywordsImpact craterEjectaVolcanoGeologyExplosive materialExplosive eruptionShaped chargeProjectileSeismologyJet (fluid)PetrologyGeophysicsPyroclastic rockAstrobiologyMechanicsMaterials sciencePhysicsAstrophysics

Abstract

fetched live from OpenAlex

Most volcanic eruptions occur in craters formed by previous activity. The presence of a crater implies specific confinement geometries, variably filled by loose fragmental deposits, which are expected to exert a strong, yet poorly studied, control on the violent gas expansion that drives the eruption. Here we analyze patterns of ejection from buried explosions in analog experiments, in order to investigate how the presence of a crater and changes in explosion depth and intensity may affect the formation of eruptive ejecta jets. Results show that scaled depth (charge burial depth divided by the cubic root of charge energy) controls the velocity and, partly, spread angle of eruptive jets independently of the presence of a pre‐existing crater. Conversely, for a fixed scaled depth, the presence of a pre‐existing crater limits the development of a laterally expanding annulus of the jet. These results are directly applicable to interpretation of volcanic explosions.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.332
Teacher spread0.258 · 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 designBench or experimental
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

Citations58
Published2013
Admission routes2
Has abstractyes

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