Dingwell, Head Receive 2013 N. L. Bowen Award: Citation for Donald B. Dingwell
Bibliographic record
Abstract
It is my privilege and honor to deliver the citation for Don Dingwell to receive AGU's N. L. Bowen Award. Don's research has profoundly influenced our understanding of the properties of silicate melts, glasses, and magmas and the fundamental control they exert on magmatic, volcanic, and, recently, even on earthquake processes. Don's approach is experimental, and his studies have interrogated melts, glasses, and magmas for their transport, calorimetric, geophysical, and rheological properties, as well as the solubilities of volatile species. These experiments have been elegantly designed to elucidate properties that provide quantitative explanations for volcanic processes. He has a prodigious publication record, including many seminal “must‐read papers,” as evidenced by any bibliometrics you choose. Indeed, his research has changed the very way we communicate about volcanic processes by expanding our vocabulary to include “glass transition” or “melt relaxation.” In many ways, his research career has established what is a new, unique, and expanding line of science—“experimental volcanology.”
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.262 | 0.232 |
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".