Hydrothermal alteration and sealing at Turrialba as a mechanism for phreatic eruption triggering
Bibliographic record
Abstract
Turrialba is a basaltic to andesitic Holocene stratovolcano that after decades of quiescence re-activated in 1996 and has been highly active ever since. Turrialba is characterized by a highly active magmatic-hydrothermal system, and we propose that hydrothermal sealing and volatile accumulation are the mechanisms responsible for the reactivation and persistent phreatic activity at Turrialba since 2010. Evidence of sealing is found in pyroclastic breccias from phreatic eruptions as high concentrations of hydrothermal minerals coupled with low intrinsic permeability. The suite of volcanic breccias studied erupted from the main vent between 2014 and 2019 and has an alteration mineral assemblage of SiO2polymorphs ± gypsum ± natroalunite ± pyrite. The mineral assemblage is indicative of acid sulphate alteration within the advanced-argillic alteration facies characterized by temperatures of approximately 200-350°C as indicated by the presence of gypsum and natroalunite, the high temperature endmember of the alunite series. Acid sulphate alteration is the result of extreme base leaching by acidic fluids (pH<4) with a high sulphate content. Measurements of permeability and porosity yielded variable porosity and very low to non-existent permeability in all hydrothermal breccia samples. Back-scatter electron (BSE) images reveal nano-, micro- and macro-scale fracture networks discontinuously filled with hydrothermal gypsum and pyrite which are responsible for diminished permeability, supporting the conclusion that hydrothermal sealing is active at Turrialba. Diminished permeability associated with the formation of a seal inhibits the escape of gases, causing them to accumulate below the seal and pressurize the system. Eventual seal failure releasing overpressure and possibly dynamic rapid seal formation result in the frequent phreatic eruptions seen at Turrialba.
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 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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".