Mixing in a coastal environment: 2. A view from microstructure measurements
Bibliographic record
Abstract
During the Coastal Mixing and Optics Experiment in 1996 and 1997, an integrated dye and microstructure experiment was done to measure and compare mixing rates on the continental shelf. The results of the dye experiment are presented in the companion paper by Ledwell et al. [2004] . In this paper, we explore the results from microstructure measurements using a vertical profiling instrument. We measure temperature and velocity microstructure and, along with simultaneous measurements of salinity and temperature as well as a shipboard acoustic Doppler current profiler (ADCP), are able to estimate the vertical diffusivities of heat, mass, and momentum. In three of four dye injections performed, we were able to make a comparison of the diffusivity from both dye and microstructure measurements. Although the mixing rates were quite small (vertical diffusivity of heat, KT < 10−5 m2 s−1), the two techniques yielded consistent results. A comparison of the vertical diffusivities KT and Kρ (the vertical diffusivity for density) allowed us to determine a flux Richardson number of Rf = 0.16 ± 0.03. Rf showed little dependence on either the buoyancy frequency, N, or gradient Richardson number, Ri. A clear relationship was found between the ratio of diffusivities, Km/KT and Ri consistent with Km/KT = 5 Ri. Turbulence levels were extremely low, with Cox numbers in one experiment of about 20 and in the other three of about 5 (i.e., KT about 20 and 5 times molecular diffusion, respectively).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".