Maar‐diatreme geometry and deposits: Subsurface blast experiments with variable explosion depth
Bibliographic record
Abstract
Abstract Basaltic maar‐diatreme volcanoes, which have craters cut into preeruption landscapes (maars) underlain by downward‐tapering bodies of fragmental material commonly cut by hypabyssal intrusions (diatremes), are produced by multiple subsurface phreatomagmatic explosions. Although many maar‐diatremes have been studied, the link between explosion dynamics and the resulting deposit architecture is still poorly understood. Scaled experiments employed multiple buried explosions of known energies and depths within layered aggregates in order to assess the effects of explosion depth, and the morphology and compaction of the host on the distribution of host materials in resulting ejecta, the development of subcrater structures and deposits, and the relationships between them. Experimental craters were 1–2 m wide. Analysis of high‐speed video shows that explosion jets had heights and shapes that were strongly influenced by scaled depth (physical depth scaled against explosion energy) and by the presence or absence of a crater. Jet properties in turn controlled the distribution of ejecta deposits outside the craters, and we infer that this is also reflected in the diverse range of deposit types at natural maars. Ejecta were dominated by material that originated above the explosion site, and the shallowest material was dispersed the farthest. Subcrater deposits illustrate progressive vertical mixing of host materials through successive explosions. We conclude that the progressive appearance of deeper‐seated material stratigraphically upward in deposits of natural maars probably records the length and time scale for upward mixing through multiple explosions with ejection by shallow blasts, rather than progressive deepening of explosion sites in response to draw down of aquifers.
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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 | 0.000 | 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) | 0.001 | 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".