Bibliographic record
Abstract
Abstract The effect of multiple arms on standing wave patterns, or seiches, present within a lake is not easy to predict. This study examines free seiche modes in fjord‐type multi‐armed lakes in order to generalize features of the response of those lakes. To do so, the study develops a simplified analytical model that predicts modal frequencies and associated mode‐shapes based on idealized lake geometries. The model demonstrates that multi‐armed lakes are subject to two different types of behavior: a full‐lake response, in which all arms are active for all modes; and a decoupled response, in which seiching is constrained to only two arms of the lake for each mode. Which of the two behaviors is expressed depends on relative values of the travel time of a progressive shallow‐water wave in each arm. In general, a decoupled response will exist if the mode‐shape along a two‐armed extent of the lake contains a node exactly at the confluence point between those two arms. We show that the period and associated mode‐shape structure of the fundamental mode in multi‐armed lakes conforms to that of a simple elongated lake as predicted by Merian's formula, but higher modes are highly impacted by lake geometry. Depth and width variation within the arms can lead to localization of mode‐shapes, but this effect is distinct from the possible decoupled behavior. In some instances, it may be possible to apply the model to baroclinic modes which would then act as having a constant bottom depth equal to the surface layer depth.
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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 | 0.001 |
| 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 | 0.001 |
| 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".