Model simulated volume fluxes through the Canadian Arctic Archipelago and Davis Strait: Linking monthly variations to forcing in different seasons
Bibliographic record
Abstract
The solution of a 10 year simulation of the Arctic Ocean, produced using a 6 km resolution coupled ocean and sea-ice model, is analyzed to understand the variability, control, and forcing mechanisms of the volume fluxes through the Canadian Arctic Archipelago (CAA) and Davis Strait (DS). The analysis focuses on variability at monthly time scales. Analysis confirms the “control” of volume fluxes through the CAA, proposed in previous studies, by (1) variations of sea surface height (SSH) in the “upstream” regions and the relationship of this control to alongshore wind in the Beaufort Sea and (2) by SSH in the “downstream” region in Baffin Bay that may be related to wind stress in Baffin Bay and the northern Labrador Sea. The effectiveness of these control and forcing mechanisms vary for fluxes through different sections and for different seasons. Variation of the southward flux through DS is directly influenced by fluxes through Nares Strait (NS) and Barrow Strait (BS) in summer, fall, and winter. In spring, variations of the southward and northward fluxes through DS are closely related to each other and correspond to changes in the SSH along pathways of the Irminger Current, and the East and West Greenland Currents.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".