Bibliographic record
Abstract
Abstract Optimal observations are used to investigate the overturning streamfunction in the North Atlantic at 30°N and 900-m depth. Those observations are designed to impact the meridional overturning circulation (MOC) in numerical models maximally when assimilated and therefore establish the most efficient observation network for studying changes in the MOC. They are also ideally suited for studying the related physical mechanisms in a general circulation model. Optimal observations are evaluated here in the framework of a global 1° model over a 10-yr period. Hydrographic observations useful to monitor the MOC are primarily located along the western boundary north of 30°N and along the eastern boundary south of 30°N. Additional locations are in the Labrador, Irminger, and Iberian Seas. On time scales of less than a year, variations in MOC are mainly wind driven and are made up through changes in Ekman transport and coastal up- and downwelling. Only a small fraction is buoyancy driven and constitutes a slow response, acting on time scales of a few years, to primarily wintertime anomalies in the Labrador and Irminger Seas. Those anomalies are communicated southward along the west coast by internal Kelvin waves at the depth level of Labrador Sea Water. They primarily set the conditions at the northern edge of the MOC anomaly. The southern edge is mainly altered through Rossby waves of the advective type, which originate from temperature and salinity anomalies in the Canary Basin. Those anomalies are amplified on their way westward in the baroclinic unstable region of the subtropical gyre. The exact meridional location of the maximum MOC response is therefore set by the ratio of the strength of these two signals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".