Using Drones and Miniaturized Instrumentation to Study Degassing at Turrialba and Masaya Volcanoes, Central America
Bibliographic record
Abstract
Abstract Gas measurements using unmanned aerial vehicles, or drones, were undertaken at Turrialba volcano, Costa Rica, and Masaya volcano, Nicaragua, in 2016 and 2017. These two volcanoes are the largest time‐integrated sources of gas in the Central American Volcanic Arc, and both systems are currently extremely active with potential for sudden destabilization. We employed a series of miniaturized drone‐mounted instrumentation including a mini‐DOAS, two MultiGAS instruments, and an optical particle counter, supplemented by ground‐based measurements. Payloads were typically 1–1.5 kg and flight times were 10–15 min. The measurements were both accurate and precise due to the inherent sensitivity of the instrumentation and the high gas concentrations, which the drones were able to sample. The quality of data obtained by our drones was comparable to that obtained by our ground‐based measurements. At Turrialba in April 2017, we measured an average SO 2 flux of 1,380 ± 280 T/day, CO 2 /SO 2 of 6.5, and H 2 O/SO 2 of 27.8. Using these values, we calculated a CO 2 flux of 6,170 T/day and an H 2 O flux of 10,790 T/day. At Masaya in May 2017, the average SO 2 flux was 1,560 ± 180 T/day, with CO 2 /SO 2 of 3.9 and H 2 O/SO 2 of 62.3, giving a mean CO 2 flux of 4,150 T/day and mean H 2 O flux of 27,330 T/day. The elevated carbon and water fluxes and ratios are indicative of underlying magmas that are enriched in these components, resulting in the high levels of activity observed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".