Modelling deep seasonal temperature changes in the Labrador Sea
Bibliographic record
Abstract
An eddy‐admitting model of the North Atlantic is applied to study the seasonal variations of temperature at 1000 m in the Labrador Sea. The model successfully reproduces the seasonal cycle of the near‐bottom temperature observed from a long‐term mooring deployed on the 1000 m isobath on the upper continental slope off Labrador. It also provides an estimate of the spatial distribution of the seasonal temperature variation in the whole Labrador Sea that can be interpreted in terms of the roles played by surface cooling, deep convection, lateral mixing and advection. The model results suggest that mixing along the steeply sloped isopycnal surfaces plays an important role in communicating the cold water formed by surface cooling to deep layers over the Labrador Slope in later winter. Upstream conditions are also communicated to the mooring site along the Slope through advection by the prevailing cyclonic circulation. In particular, the advection of warm water off Greenland contributes to the gradual warming from spring to winter at the mooring site.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".