Lava and ice interaction at stratovolcanoes: Use of characteristic features to determine past glacial extents and future volcanic hazards
Bibliographic record
Abstract
Structures resulting from lava and ice interaction are common at glaciated stratovolcanoes. During summit eruptions at stratovolcanoes, meltwater is produced and travels freely down steep slopes and thin permeable valley glaciers, eroding the ice and enlarging preexisting glacial drainages. As a result, eruptions in this environment have produced few catastrophic floods. Lava flowing into the open channels and voids in the glaciers becomes confined and grows thicker, filling the available space and producing steep‐sided bodies with smooth, bulbous contact surfaces. Quenching of lava against ice or by water forms small‐scale features such as tensional fractures and glass. As the amount of meltwater in contact with the lava increases, the type and abundance of smaller‐scale features become similar to those produced during subglacial eruptions into meltwater lakes. Identification of large‐ and small‐scale lava‐ice contact features in the field can be used to reconstruct paleoglacial extent and, combined with geochronology of lavas, to determine past paleoclimate. An understanding of lava‐ice interaction allows us to better assess the hazards posed by future eruptions at glaciated volcanoes.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".