Age of the magma chamber and its physicochemical state under Elbrus Greater Caucasus, Russia using zircon petrochronology and modeling insights
Bibliographic record
Abstract
Abstract Mount Elbrus, Europe's tallest and largely glaciated volcano, is made of silicic lavas and is known for Holocene eruptions, but the size and state of its magma chamber remain poorly constrained. We report high spatial resolution U–Th–Pb zircon ages, co-registered with oxygen and hafnium isotopic values, span ~ 0.6 Ma in each lava, documenting magmatic initiation that forms the current edifice. The best-fit thermochemical modeling constrains magmatic fluxes at 1.2 km 3 /1000 year by hot (900 °C), initially zircon-undersaturated dacite into a vertically extensive magma body since ~ 0.6 Ma, whereas a volcanic episode with eruptible magma only extends over the past 0.2 Ma, matching the age of oldest lavas. Simulations explain the total magma volume of ~ 180 km 3 , temporally oscillating δ 18 O and εHf values, and a wide range of zircon age distributions in each sample. These data provide insights into the current state (~ 200 km 3 of melt in a vertically extensive system) and the potential for future activity of Elbrus calling for much-needed seismic imaging. Similar zircon records worldwide require continuous intrusive activity by magmatic accretion of silicic magmas generated at depths, and that zircon ages do not reflect eruption ages but predate them by ~ 10 3 to 10 5 years reflecting protracted dissolution–crystallization histories.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".