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Record W4417454390 · doi:10.1038/s41598-025-30551-y

Comment on “Volcanic monitoring of the 2021 La Palma eruption using long-period magnetotelluric data”

2025· letter· en· W4417454390 on OpenAlexaff
Darcy Cordell, Graham J. Hill, Max Moorkamp, Stephan Thiel

Bibliographic record

VenueScientific Reports · 2025
Typeletter
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsAthabasca UniversityUniversity of Alberta
Fundersnot available
KeywordsMagnetotelluricsInverse theoryMEDLINE

Abstract

fetched live from OpenAlex

Tracking changes in electrical resistivity structure at volcanoes as a monitoring method using magnetotelluric (MT) data is an important goal which has been shown to have significant benefits for understanding magmatic systems 1 , 2 , 3 , 4 , 5 . However, as with any developing method, care must be taken to ensure robust results. We believe that the recent study by Ref. 6 (herein referred to as PV23) lacks sufficient evidence to support the claim that observed temporal variations in MT data are due to active processes within the crustal magmatic system. Below, we argue that the temporal variations shown in PV23 are not due to deep magmatic processes related to the Dec. 2021 eruption on La Palma and are instead due to problems with the geoelectric field data quality likely related to electrode instability along a single dipole. The fact that the observed temporal variations are not due to deep magmatic processes significantly undermines the interpretation and conclusions of PV23.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.518
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.253
Teacher spread0.220 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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