Phreatic and Hydrothermal Eruptions: From Overlooked to Looking Over
Bibliographic record
Abstract
Abstract Over the last decade, field investigations, laboratory experiments, geophysical exploration and petrological, geochemical and numerical modelling have provided insight into the mechanisms of phreatic and hydrothermal eruptions. These eruptions are driven by sudden flashing of ground- or hydrothermal water to steam and are strongly influenced by the interaction of host rock and hydrothermal system. Aquifers hosted in volcanic edifices, calderas and rift environments can be primed for instability by alteration processes affecting rock permeability and/or strength, while magmatic fluid injection(s), earthquakes or other subtle triggers can promote explosive failure. Gas emission, ground deformation and seismicity may provide short- to medium-term forerunner signals of these eruptions, yet a definition of universal precursors remains a key challenge. Looking forward in the next 10 years, improved warning and hazard assessment will require integration of field and experimental data with models combining case studies, as well as development of new monitoring methods integrated by machine learning approaches.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.043 | 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".