Bibliographic record
Abstract
Ocean convection in the Antarctic has been studied many times and has been revealed to be responsible for ice-cover reduction. In the Arctic, proof of that phenomenon has not been documented. It is believed that this phenomenon happens on a smaller scale in the Arctic when local circulation of deep warmer water melts and slows ice production. An example of this is the North Water (NOW) polynya in northern Baffin Bay. A polynya is an area of open water in an otherwise ice-covered area. As ice forms under the fast ice near the boundary of the polynya, ocean salts (brine) are ejected from the newly formed ice. This water, which has an increased concentration of salt, sinks and is replaced by warmer water from below, and this slows ice formation. In our study a coupled one-dimensional thermodynamic snow–fast ice model incorporating ocean heat flux input via a shallow convection model was used. Ice thickness was calculated using a thermodynamic model that included a current-induced entrainment model and a convection model to account for brine rejection during ice growth. Atmospheric observations from Grise Fiord and Thule and ocean profiles around the NOW polynya near these sites were used as input to the model. This purely thermodynamic study enables us to obtain ice thickness values that can be compared with qualitative observations. This modelling study compares two sites related to the NOW polynya. The results indicate that the shallow convection model simulates the reduction of fast ice near Thule but not near Grise Fiord.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".