Convectively driven transport in temperate lakes
Bibliographic record
Abstract
Penetrative convection in the surface layer of a midsize temperate lake (5 km2) was investigated in both summer and winter using a conductivity‐temperature‐depth (CTD) logger mounted on an autonomous underwater vehicle (AUV) flown repeatedly along horizontal transects at selected depths. In summer, the epilimnion cooled differentially during a calm evening (240 and 297 W m−2 on the east and west sides of the lake, respectively). These cooling rates agree well with the average net heat flux of 270 W ths. In summer, the epilimnion cooled differentially during a calm evening (240 and 297 W estimated from meteorological data. Density currents were driven by this differential cooling. In winter, CTD profiles during a sunny day showed four distinct thermal layers beneath the ice (~50 cm thick), consistent with radiative penetrative convection: a stratified diffusive layer just beneath the ice (top 1.6 m); a well‐mixed convective layer (that deepens at 1.14 m d−1 and warms at 0.015°C d−1 during the observation period); an entrainment layer (1.5 m thick); and a weakly stratified quiescent layer (to bottom). AUV transects, flown at constant depths in each layer, revealed a 150‐m wide region displaying evidence of penetrative convection, surrounded by regions with negligible heat changes. These high‐resolution, horizontal CTD measurements provided insight into previously unresolved physical dynamics of the well‐mixed layer of a temperate lake in quasi‐shear‐free conditions that would have been difficult to quantify during summer months and impossible under winter ice cover without the use of an AUV platform.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".