Behavior and Passage Performance of Northern Pike, Walleyes, and White Suckers in an Experimental Raceway
Bibliographic record
Abstract
Abstract The willingness and ability of wild adult northern pike Esox lucius, walleyes Sander vitreus, and white suckers Catostomus commersonii to ascend a 25- or 50-m experimental raceway against various water velocities (35–120 cm/s at 8 cm from the bottom) was measured. The probability that a fish of any given species would enter the raceway from its holding tank was significantly correlated with fork length, water temperature, and tank volume but was not correlated with water velocity. On average, 62.6% of northern pike, 45.0% of walleyes, and 44.2% of white suckers entered volitionally. For those fish that entered, the probability that at least one complete ascent would occur during the exposure period was not dependent on fish length, water temperature, raceway length, duration of the exposure period, time in captivity, or water velocity. On average, 74.4% of northern pike, 76.4% of walleyes, and 77.3% of white suckers that entered the raceway made at least one complete ascent. For northern pike and walleyes, the proportion of successful ascents at the highest water velocity tested (120 cm/s) was significantly lower than the proportions observed at the lower velocities. No significant differences were found among ascent proportions for white suckers. Fish in general may be more inclined to enter a culvert if the pool downstream of the entrance is relatively small. Culverts less than 50 m long should allow these species to pass as long as water velocities near the bottom do not exceed 100 cm/s. Fish passage models based on published data from forced performance trials predicted lower maximum allowable water speeds, which adds to a growing body of work that indicates the unsuitability of these tests for use in setting velocity criteria in culverts and fishways.
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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 | 0.000 |
| 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".