Percolating magmas and explosive volcanism
Why this work is in the frame
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Bibliographic record
Abstract
Magma under pressure rises in conduits, depressurizes, forms bubbles by the exsolution of gas and – at void fractions ( P ) typically of the order of 0.7 – can fragment and explode. The study of overlapping geometrical units – percolation theory – predicts that at a critical volume fraction P c the size of the largest simply connected region becomes infinite. We apply percolation theory to overlapping bubbles arguing that this geometric singularity at P c implies a physical singularity in the magma rheology. This would imply that if the magma is under stress, ‐ whether it is ductile or brittle ‐ this rapid development of a network of infinitely long “bubbles” triggers fragmentation and explosion. Classical monodisperse (equal size) continuum percolation theory predicts P c = 0.2985 ± 0.005 which is far from the observed values. However, it has recently been shown that the bubble distribution is a power law associated with a huge range of bubble sizes. Using Monte Carlo percolation simulations, we show that distributions exhibiting the empirical exponents are very efficient at “packing” the bubbles, drastically raising P c to the value = 0.70 ± 0.05. Explosive volcanism is thus explained by singular rheology at P c .
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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) | 0.000 | 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 it