Bibliographic record
Abstract
Abstract Argo floats are used to investigate Labrador Sea overturning and its variability on seasonal time scales. This is the first application of Argo floats to estimate overturning in a deep-water formation region in the North Atlantic. Unlike hydrographic measurements, which are typically confined to the summer season, floats offer the advantage of collecting data in all seasons. Seasonal composite potential density and absolute geostrophic velocity sections across the mouth of the Labrador Sea assembled from float profiles and trajectories at 1000 m are used to calculate the horizontal and overturning circulations. The overturning exhibits a pronounced seasonal cycle; in depth space the overturning doubles throughout the course of the year, and in density space it triples. The largest overturning [1.2 Sv (1 Sv ≡ 106 m3 s−1) in depth space and 3.9 Sv in density space] occurs in spring and corresponds to the outflow of recently formed Labrador Sea Water. The overturning decreases through summer and reaches a minimum in winter (0.6 Sv in depth space and 1.2 Sv in density space). The robustness of the Argo seasonal overturning is supported by a comparison to an overturning estimate based on hydrographic data from the AR7W line.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".