New insights into the relationship between mass eruption rate and volcanic column height based on the IVESPA dataset
Bibliographic record
Abstract
Relating the mass eruption rate (MER) of explosive eruptions to column height in the atmosphere is key to reconstructing past eruptions and forecasting volcanic hazards. Using 134 eruptive events from the Independent Volcanic Eruption Source Parameter Archive (IVESPA v1.0), we explore the canonical MER-height relationship for four measures of column height: spreading level, sulfur dioxide height, and top height from both directly observed plumes and those reconstructed from deposits. These relationships show significant differences and should be chosen carefully for operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to assess across the large range of eruptive conditions in this database, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding reveals the complexity of the height-MER relation that is difficult to constrain based on available heterogeneous observations, which reinforces the need for improved datasets to develop eruptive column models.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".