A Permanent, Real-Time Monitoring Network for the Volcanoes Mount Scenery and The Quill in the Caribbean Netherlands
Bibliographic record
Abstract
The stratovolcanoes of Mt. Scenery at Saba and The Quill at St. Eustatius in the Caribbean Netherlands, with a total population of about 5200 people, are part of the active volcanic arc of the Lesser Antilles but lacked a multiparameter volcano and earthquake monitoring system until the beginning of 2018. The permanent seismic network on the islands has been built up since 2006 and was expanded in 2018 with one permanent Global Navigation Satellite System (GNSS) sensor at each volcano and a temperature logger on Saba. We provide technical details of all equipment and the installation procedures, and we show the preliminary results of GNSS data processing. Deploying a remote, permanent network of different sensor types under tropical island conditions and sustaining access to real-time high-quality data to monitor the state of volcanoes is an underappreciated challenge. Despite the problems encountered, we operated the network with an overall availability of 84.5% in the first half of 2018 compared to 70.3% in the years before. The main unresolved problem affecting seismic data quality is related to sudden out-of-balance seismometer mass positions. We provide a complete overview of our monitoring network, the various challenges encountered, and the solutions applied, and we address future plans.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".