Carbon isotope systematics of <scp>T</scp>urrialba volcano, <scp>C</scp>osta <scp>R</scp>ica, using a portable cavity ring‐down spectrometer
Bibliographic record
Abstract
Abstract Over the past two decades, activity at Turrialba volcano, Costa Rica, has shifted from hydrothermal to increasingly magmatic in character, with enhanced degassing and eruption potential. We have conducted a survey of the δ13C signatures of gases at Turrialba using a portable field‐based CRDS with comparison to standard IRMS techniques. Our δ13C results of the volcanic plume, high‐temperature vents, and soil gases reveal isotopic heterogeneity in the CO2 gas composition at Turrialba prior to its recent phase of eruptive activity. The isotopic value of the regional fault system, Falla Ariete (–3.4 ± 0.1‰), is in distinct contrast with the Central crater gases (–3.9 ± 0.1‰) and the 2012 high‐temperature vent (–4.4 ± 0.2‰), an indication that spatial variability in δ13C may be linked to hydrothermal transport of volcanic gases, heterogeneities in the source composition, or magmatic degassing. Isotopic values of CO2 samples collected in the plume vary from δ13C of −5.2 to −10.0‰, indicative of mixing between atmospheric CO2 (–9.2 ± 0.1‰), and a volcanic source. We compare the Keeling method to a traditional mixing model (hyperbolic mixing curve) to estimate the volcanic source composition at Turrialba from the plume measurements. The predicted source compositions from the Keeling and hyperbolic methods (–3.0 ± 0.5‰ and −3.9 ± 0.4‰, respectively) illustrate two potential interpretations of the volcanic source at Turrialba. As of the 29 October 2014, Turrialba has entered a new eruptive period, and continued monitoring of the summit gases for δ13C should be conducted to better understand the dominant processes controlling δ13C fractionation at Turrialba.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".