Downstream Migration of Atlantic Salmon Smolts Through Fishpass Designed for Upstream Migration of Adult Spawners
Bibliographic record
Abstract
ABSTRACT Efficient fish migration is vital for anadromous species navigating between freshwater spawning/rearing habitats and oceanic feeding grounds. Mitigation measures past artificial barriers that secure two‐way fish migration at hydropower plants are complex, especially securing safe and efficient downstream migration to the ocean from freshwater. The primary efforts made have been to attract fish towards safe downstream bypasses with a diverse suite of guidance structures. However, comparatively less emphasis has been placed on a conveyance structure that ensures the safe and effective transport of fish further downstream. This study investigates if fishpass designed for upstream migration can function as an effective downstream conveyance structure. Two common fishpass types, vertical slot and pool and weir, were examined using PIT‐tagged wild Atlantic salmon smolts. Downstream progression through the vertical slot fishpass was significantly faster than through the pool and weir fishpass ( p < 0.001). The average progression rate was 3.4 m per hour or 0.0067 body lengths per second. Slower progression rates beyond passages may have ecological consequences. Delayed smolt migration could lead to predation risks, higher energy costs, and changes in migration patterns. To optimize smolt migration, alternative solutions such as pipes or channels should be considered, between the bypass entrance and the downstream facility.
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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) | 0.001 | 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".