Bibliographic record
Abstract
Abstract Calving from the floating termini of outlet glaciers and ice shelves is just the beginning of an interesting chain of events that can subsequently have important impacts on human life and property. Immediately after calving, many icebergs capsize (roll over by 90°) due to the instability of their initial geometry. As icebergs melt and respond to the cumulative effects of ocean swell, they can also reorient their mass distribution by further capsize and fragmentation. These processes release gravitational potential energy and can produce impulsive large-amplitude surface-gravity waves known as tsunamis (a term derived from the Japanese language). Iceberg-capsize tsunamis in Greenland fjords can be of sufficient amplitude to threaten human life and cause destruction of property in settlements. Iceberg-capsize tsunamis may also have a role in determining why some ice shelves along the Antarctic Peninsula disintegrate ‘explosively’ in response to general environmental warming. To quantify iceberg tsunami hazards we investigate iceberg-capsize energetics, and develop a rule relating tsunami height to iceberg thickness. This rule suggests that the open-water tsunami height (located far from the iceberg and from shorelines where the height can be amplified) has an upper limit of 0.01H where H is the initial vertical dimension of the iceberg.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".