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Record W4387164927 · doi:10.1126/sciadv.adi2698

Insights into dike nucleation and eruption dynamics from high-resolution seismic imaging of magmatic system at the East Pacific Rise

2023· article· en· W4387164927 on OpenAlexaff
M. Marjanović, S. M. Carbotte, Alexandre Stopin, S. C. Singh, René-Édouard Plessix, Miloš Marjanović, M. R. Nedimović, J. P. Canales, H. D. Carton, John C. Mutter, J. Escartı́n

Bibliographic record

VenueScience Advances · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGeologyDikeMagmaVolcanoMagma chamberSeafloor spreadingSeismologyLateral eruptionPetrologyGeophysicsGeochemistryExplosive eruption

Abstract

fetched live from OpenAlex

Models of magmatic systems suggest that the architecture of crustal magma bodies plays an important role in where volcanic eruptions occur, but detailed field observations are needed to evaluate them. We present ultrahigh-resolution reflection images of magma bodies beneath a region of multiple eruptions along the East Pacific Rise derived from three-dimensional seismic surveying. The observations reveal magma bodies with elongate ridges and troughs vertically aligned with seafloor eruptive fissures that we interpret as remnant dike root zones where repeat dikes nucleate. We document a triangular feeder zone to the axially centered magma body from the off-axis source for a newly forming seamount of the Lamont chain and infer bottom-up eruption triggering due to recharge from this deeper source. The findings indicate that magma bodies are sculpted by both processes of magma recharge from below and magma extraction to the surface, leaving a morphological imprint that contributes to localization of dike nucleation and eruption sites at the East Pacific Rise.

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)0.000
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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