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Record W2049957311 · doi:10.1007/s00445-014-0885-8

Kawah Ijen volcanic activity: a review

2015· review· en· W2049957311 on OpenAlexaff
Corentin Caudron, Devy Kamil Syahbana, Thomas Lecocq, Vincent van Hinsberg, Wendy McCausland, Antoine Triantafyllou, Thierry Camelbeeck, Alain Bernard, Surono Surono

Bibliographic record

VenueBulletin of Volcanology · 2015
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsVolcanoUnrestGeologySedimentologySeismologyEarth scienceCalderaJavaPhysical geographyPaleontologyGeography

Abstract

fetched live from OpenAlex

Kawah Ijen is a composite volcano located at the easternmost part of Java island in Indonesia and hosts the largest natural acidic lake in the world. We have gathered all available historical reports on Kawah Ijen’s activity since 1770 with the purpose of reviewing the temporal evolution of its activity. Most of these observations and studies have been conducted from a geochemical perspective and in punctuated scientific campaigns. Starting in 1991, the seismic activity and a set of volcanic lake parameters began to be weekly available. We present a database of those measurements that, combined with historical reports, allow us to review each eruption/unrest that occurred during the last two centuries. As of 2010, the volcanic activity is monitored by a new multi-disciplinary network, including digital seismic stations, and lake level and temperature measurements. This detailed monitoring provides an opportunity for better classifying seismic events and forecasting volcanic unrest at Kawah Ijen, but only with the understanding of the characteristics of this volcanic system gained from the historical review presented here.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.062
GPT teacher head0.287
Teacher spread0.225 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations64
Published2015
Admission routes1
Has abstractyes

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