Estimation of Horizontal Eddy Heat Flux in Upper Mixed-Layer in the South China Sea by Using Satellite Data
Bibliographic record
Abstract
In this study, the horizontal eddy heat flux in the upper mixed-layer in the South China Sea (SCS) is derived from satellite-derived observational data of sea surface height anomalies and optimally interpolated sea surface temperature, as well as a reanalysis dataset of mixed-layer depth. The long-term heat flux shows a northward transport on the west side of the SCS, comparable with that in the Kuroshio extension with strong eddy activities. The eddy flux in the SCS has a prominent semi-annual cycle and becomes the strongest in winter and summer with the inflow flux in the south and the outflow in the northwest into the East China Sea through the Taiwan Strait. The semi-annual cycle is related to the strong semi-annul variabilities of the velocity and the temperature in areas southeast of Vietnam and in the northern SCS, respectively. In some areas of the SCS, the eddy heat flux can reach more than ~ 60% of the mean flow heat flux. The convergence of the eddy flux indicates that heat accumulates southeast of Vietnam, which may result in heat storage increases in the upper mixed-layer.
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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) | 0.001 | 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) | 0.000 | 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".