Fragmentation patterns of Antarctic icebergs in sea ice: observations and statistical data
Bibliographic record
Abstract
Fragmentation is a key process in Antarctic iceberg decay, influencing the Antarctic climate and ecosystems. However, iceberg fragmentation has not been quantified at the pan-Antarctic scale. Using Sentinel-1 data from August to October 2019, we identified 407 fragmentation events in the circum-Antarctic near-coastal zone, with original iceberg sizes ranging from 0.01 km² to 5591.34 km². The Indian Ocean sector had the greatest number of fragmented events, 97% of which involved icebergs less than 1 km², whereas the Bellingshausen–Amundsen Sea sector has experienced the highest number of fragmentation events involving medium to large icebergs. Smaller icebergs (less than 1 km²) were more susceptible to disintegration through highly fractured capsizing, whereas larger icebergs underwent disarticulation. Fragmentation events were less frequent in landfast ice or mélange (∼0.5% monthly), whereas icebergs exceeding 10 km² exhibited a notable increase in the ratio of fragmentation events to the total number of icebergs (more than 15% monthly) when they were in motion and rotating in pack ice. Our findings indicate that during winter and under extensive sea ice cover, internal ocean waves, ocean currents and collisions are key factors influencing iceberg fragmentation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".