Pathways, Volume Transport, and Mixing of Abyssal Water in the Samoan Passage
Bibliographic record
Abstract
Abstract The flow of dense water through the Samoan Passage accounts for the major part of the bottom water renewal in the North Pacific and is thus an important element of the Pacific meridional overturning circulation. A recent set of highly resolved measurements used CTD/LADCP, a microstructure profiler, and moorings to constrain the complex pathways and variability of the abyssal flow. Volume transport estimates for the dense northward current at several sections across the passage, calculated using direct velocity measurements from LADCPs, range from 3.9 × 106 to 6.0 × 106 ± 1 × 106 m3 s−1. The deep channel to the east and shallower pathways to the west carried about equal amounts of this volume transport, with the densest water flowing along the main eastern channel. Turbulent dissipation rates estimated from Thorpe scales and direct microstructure agree to within a factor of 2 and provide a region-averaged value of O(10−8) W kg−1 for layers colder than 0.8°C. Associated diapycnal diffusivities and downward turbulent heat fluxes are about 5 × 10−3 m2 s−1 and O(10) W m−2, respectively. However, heat budgets suggest heat fluxes 2–6 times greater. In the vicinity of one of the major sills of the passage, highly resolved Thorpe-inferred diffusivity and heat flux were over 10 times larger than the region-averaged values, suggesting the mismatch is likely due to undersampled mixing hotspots.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".