Bibliographic record
Abstract
A broadband ADCP and a moored microstructure instrument (TAMI) were deployed in a tidal channel of 30-m depth and with peak speeds of 1 m s−1. The measurements enable us to derive profiles of stress, turbulent kinetic energy (TKE), the rate of production and dissipation of TKE, eddy viscosity, diffusivity, as well as mixing length, and to test the parameterization of dissipation rate in the model of Mellor and Yamada. At middepth in the channel where the influence of stratification was present, the Ellison length agrees with the Ozmidov length. The measured mixing length is smaller than the simple z-dependence formulation proposed for unstratified turbulence. The diffusivity of density and heat, and the viscosity for momentum, are correlated and comparable in magnitudes. The 20-min averaged production rate deduced from the ADCP agrees with the dissipation rate estimated from microstructure measurements. The dissipation rate calculated with the Mellor–Yamada model agrees with the measured values with TAMI, but the empirical constant B1 derived from the data is larger than that conventionally used in the model. In the near-bottom layer, there is a tight correlation between the production rate and the closure-based dissipation rate. The Reynolds stress at 3.6 m above the bottom is consistently 2.5 times smaller than the shear velocity squared (u2∗), which is inferred from fitting the velocity profiles to a logarithmic form. A logarithmic velocity profile almost always exists and reaches heights of 5.6 to 20 m, but the Reynolds stress is seldom constant in any part of the logarithmic 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) | 0.000 | 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".