Sensitive Temperature Probes Detail Different Turbulence Processes in the Deep Mediterranean
Bibliographic record
Abstract
In addition to large-scale water flows and eddies, small-scale turbulent mixing distributes heat, water masses, and suspended matter in the deep sea. In contrast to turbulent mixing near the sea surface, which is driven by wind and waves and redistributes solar heat input, large-scale mixing in the deep sea occurs near steep underwater topography such as ridges, seamounts, and continental slopes. For example, above the continental slope in the Western Mediterranean Sea, boundary flows, (sub-)mesoscale eddies, and internal waves dominate water motions. In this area, wintertime dense-water formation, breaking of internal waves, and geothermal heating are associated with turbulent mixing. As a result, vertical stable density stratification is very weak. Detailed observations of turbulent mixing in the deep sea are rare and demand high-resolution instrumentation. This paper provides an overview of various types of deep Mediterranean turbulence observed using high-resolution temperature sensors, including weak turbulence resulting from stable internal waves in late summer and autumn, strong turbulence caused by geothermal heating from below in winter, and moderate turbulence induced by stratified waters pressing down from above during dense-water formation in late winter and spring.
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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 | 0.000 | 0.000 |
| 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".