Finescale parameterizations of turbulent dissipation
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Bibliographic record
Abstract
Abstract This article (1) reviews and clarifies the basic physics underpinning finescale parameterizations of turbulent dissipation due to internal wave breaking and (2) provides advice on the implementation of the parameterizations in a way that is most consistent with the underlying physics, with due consideration given to common instrumental issues. Potential biases in the parameterization results are discussed in light of both (1) and (2), and illustrated with examples in the literature. The value of finescale parameterizations for studies of the large‐scale ocean circulation in the presence of common biases is assessed. We conclude that the parameterizations can contribute significantly to the resolution of large‐scale circulation problems associated with plausible ranges in the rates of turbulent dissipation and diapycnal mixing spanning an order of magnitude or more.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it