Magma Reservoir Below Laguna del Maule Volcanic Field, Chile, Imaged With Surface‐Wave Tomography
Bibliographic record
Abstract
Abstract The Laguna del Maule (LdM) volcanic field comprises the greatest concentration of postglacial rhyolite in the Andes and includes the products of ~40 km3 of explosive and effusive eruptions. Recent observations at LdM by interferometric synthetic aperture radar and global navigation satellite system geodesy have revealed inflation at rates exceeding 20 cm/year since 2007, capturing an ongoing period of growth of a potentially large upper crustal magma reservoir. Moreover, magnetotelluric and gravity studies indicate the presence of fluids and/or partial melt in the upper crust near the center of inflation. Petrologic observations imply repeated, rapid extraction of rhyolitic melt from crystal mush stored at depths of 4–6 km during at least the past 26 ka. We utilize multiple types of surface‐wave observations to constrain the location and geometry of low‐velocity domains beneath LdM. We present a three‐dimensional shear‐wave velocity model that delineates a ~450‐km3 shallow magma reservoir ~2 to 8 km below surface with an average melt fraction of ~5%. Interpretation of the seismic tomography in light of existing gravity, magnetotelluric, and geodetic observations supports this model and reveals variations in melt content and a deeper magma system feeding the shallow reservoir in greater detail than any of the geophysical methods alone. Geophysical imaging of the LdM magma system today is consistent with the petrologic inferences of the reservoir structure and growth during the past 20–60 kyr. Taken together with the ongoing unrest, a future rhyolite eruption of at least the scale of those common during the Holocene is a reasonable possibility.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".