Ash production by attrition in volcanic conduits and plumes
Bibliographic record
Abstract
Tephra deposits result from explosive volcanic eruption and serve as indirect probes into fragmentation processes operating in subsurface volcanic conduits. Primary magmatic fragmentation creates a population of pyroclasts through volatile-driven decompression during conduit ascent. In this study, we explore the role that secondary fragmentation, specifically attrition, has in transforming primary pyroclasts upon transport in volcanic conduits and plumes. We utilize total grain size distributions from a suite of natural and experimentally produced tephra to show that attrition is likely to occur in all explosive volcanic eruptions. Our experimental results indicate that fine ash production and surface area generation is fast (<15 min) thereby rapidly raising the fractal dimension of tephra deposits. Furthermore, a new metric, the Entropy of Information, is introduced to quantify the degree of attrition (secondary fragmentation) from grain size data. Attrition elevates fine ash production which, in turn, has consequences for eruption column stability, tephra dispersal, aggregation, volcanic lightening generation, and has concomitant effects on aviation safety and Earth's climate.
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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) | 0.000 | 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 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".