If you build it, will they pass? A systematic evaluation of fish passage efficiency for three large-bodied warm-water fishes
Bibliographic record
Abstract
Fish passages are constructed to facilitate movement around barriers, but few are quantitatively evaluated for non-salmonids. We quantified the efficiency of a selective, nature-like fish passage for three native fishes, Colorado pikeminnow ( Ptychocheilus lucius), flannelmouth sucker ( Catostomus latipinnis), and razorback sucker ( Xyrauchen texanus), in the San Juan River, NM, USA, by estimating the probabilities of completing three navigational phases and associated delay times. We compared passage efficiency in years when fish were captured in a trap and manually moved upstream to years when the trap was removed in the spring. All species were less efficient at navigating the attraction and exit phases compared with the ascent phase. Operating the passage without the trap generally increased passage success and shortened delay times. The mean probability of passage and delay time among species when the trap was removed ranged from 34%–55% and 5–21 days, respectively. Our results suggest species- and phase-specific variation in passage efficiency and highlight the need for evaluations to aid future passage design and operation for a greater diversity of fish.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".