Bibliographic record
Abstract
High‐resolution three‐dimensional numerical modeling and field observations were used to describe the nonlinear response of Cayuga Lake to surface wind forcing. The degeneration of the basin‐scale internal wave field was characterized according to the composite Froude number ( G 2 ), Wedderburn number ( W N ), and Lake number ( L N ), which are measures of hydraulic control and bulk and integral wind disturbance force to the baroclinic restoring force, respectively. The typical Cayuga Lake response was a nonlinear surge when ∼ 1 < W N (or L N ) < ∼ 2–12 and a surge with emergent nonlinear internal waves when W N or L N < ∼ 2, in agreement with published laboratory studies. An observed shock front was simulated to be an internal hydraulic jump, occurring at midbasin during strong winds when W N < 0.8. To our knowledge, this is the first simulation of a midbasin seiche‐induced hydraulic jump (supported by field data) due to supercritical conditions ( G 2 > 1) in a lake. The occurrence of the hydraulic jump was correctly predicted using scaling parameters. It was also shown that topographically induced internal hydraulic jumps form when the nonlinear surges interact with a sill‐contraction topographic feature. In contrast to published literature, the observed high‐frequency nonlinear internal waves were preferentially associated with internal jumps, as opposed to steepened internal surges. Computed vertical diffusivities showed mixing was enhanced by two orders of magnitude within both the surges and hydraulic jumps as they propagated through the basin and interacted with topography. Our results can be generalized to other lakes and fjords with similar long‐narrow geometry and topographically separate side basins.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".