Bibliographic record
Abstract
Abstract This paper introduces modifications to the traditional viscous‐plastic sea‐ice dynamical model, which are necessary to model land‐fast ice in the Kara Sea in a realistic manner. The most important modifications are an increase in the maximum viscosity from the standard value of to , and to use a solver for the momentum equation capable of correctly solving for small ice velocities (the limit here is set to m/s). Given these modifications, a necessary condition for a realistic fast‐ice simulation is that the yield curve give sufficient uniaxial compressive strength. This is consistent with the idea that land‐fast ice in the Kara Sea forms primarily via static arching. The modified model is tested and tuned using forcing data and observations from 1997 and 1998. The results show that it is possible to model land‐fast ice using this model with the modifications mentioned above. The model performs well in terms of modeled fast‐ice extent, but suffers from unrealistic break‐ups during the start and end of the fast‐ice season. The main results are that fast ice in the Kara Sea is supported by arching of the ice, the arches footers resting on a chain of islands off shore.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".