Bibliographic record
Abstract
We provide the first in situ observations of floe size distributions (FSD) resulting from wave-induced sea ice break-up. In order to obtain such data, an unmanned aerial vehicle was deployed from the Canadian Coast Guard Ship Amundsen as it sailed in the vicinity of large ice floes in Baffin Bay and in the St. Lawrence Estuary, Canada. When represented as probability density functions weighted by the surface of ice floes, the FSDs exhibit a strong modal shape which confirms the preferential size hypothesis debated in the scientific community. Both FSDs are compared to a flexural rigidity length scale, which depends on ice properties, and with the wavelength scale. This comparison tends to show that the maximal distance between cracks is preferentially dictated by sea ice thickness and elasticity rather than by the wavelength. Temporal analysis of one fracture event is also done. Results show that the break-up advances almost as fast as the wave energy and that waves responsible for the break-up propagate following the mass loading dispersion relation. Moreover, our experiments show that thicker ice can attenuate wave less than thinner ice. This method thus provides key information on the wave-induced FSD, clarifies theoretical aspects from the construction of the FSD to its implementation in models and brings new knowledge regarding the temporal evolution of sea ice break-up.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.041 | 0.019 |
| Insufficient payload (model declined to judge) | 0.035 | 0.042 |
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".