Timescales and thermal evolution of large silicic magma reservoirs during an ignimbrite flare-up: perspectives from zircon
Bibliographic record
Abstract
Abstract Four voluminous ignimbrites (150–500 km 3 ) erupted in rapid succession at 27 Ma in the central San Juan caldera cluster, Colorado. To reconstruct the timescales and thermal evolution of these magma reservoirs, we used zircon ID-TIMS U–Pb geochronology, zircon LA-ICP-MS geochemistry, thermal modeling, and zircon age and crystallization modeling. Zircon geochronology reveals dispersed zircon age spectra in all ignimbrites, with decreasing age dispersion through time that we term a ‘chimney sweeping’ event. Zircon whole-grain age modeling suggests that 2σ zircon age spans represent approximately one-quarter of total zircon crystallization timescales due to the averaging effect of whole-grain, individual zircon ages, resulting in zircon crystallization timescales of 0.8–2.7 m.y. Thermal and zircon crystallization modeling combined with Ti-in-zircon temperatures indicates that magma reservoirs were built over millions of years at relatively low magmatic vertical accretion rates (VARs) of 2–5 × 10 –3 m y −1 (2–5 × 10 –6 km 3 y −1 km −2 ), and we suggest that such low VARs were characteristic of the assembly of the greater San Juan magmatic body. Though we cannot unequivocally discern between dispersed zircon age spectra caused by inheritance (xenocrystic or antecrystic) versus prolonged crystallization from the same magma reservoir (autocrystic), our findings suggest that long-term magma input at relatively low VARs produced thermally mature upper crustal magma reservoirs resulting in protracted zircon crystallization timescales. Compiling all U–Pb ID-TIMS zircon ages of large ignimbrites, we interpret the longer timescales of subduction-related ignimbrites as a result of longer term, lower flux magmatism, and the shorter timescales of Snake River Plain ignimbrites as a result of shorter term, higher flux magmatism.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".