The wave-drag hypothesis: an explanation for size-based lateral segregation during the upstream migration of salmonids
Bibliographic record
Abstract
During their spawning migration, large salmon, e.g., chinook (Oncorhynchus tshawytscha), swim upstream further from the bank than smaller ones, e.g., sockeye (Oncorhynchus nerka). This pattern is counterintuitive because natural selection should favor behavior that minimizes migration costs, yet by traveling further from the bank, large fish will have to swim against faster currents. Existing theory predicts that they will expend more energy than necessary as a result. One explanation for this apparently paradoxical behavior is that large fish swim further from the bank to avoid wave drag, the resistance associated with the generation of surface waves when swimming close to the surface. Wave drag was incorporated into existing theory, and the resulting model was tested to determine whether it explained size-based lateral segregation of chinook and sockeye salmon in the Nushagak River, Alaska. The wave-drag model accurately predicted the migration corridor for both species. Existing theory worked well for sockeye but not for chinook. The key to these predictions is that wave drag scales according the ratio of maximum body diameter to submergence depth, so bigger fish need to swim deeper to escape its effects.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".