The Rapid Upstream Migration of Pre-Spawn Lake Sturgeon following Trap-and-Transport over a Hydroelectric Generating Station
Bibliographic record
Abstract
Abstract Spawning migrations of Lake Sturgeon Acipenser fulvescens are often blocked by dams, and fishway designs suitable for volitional upstream passage, particularly over high-head structures, remain elusive. Trap-and-transport has potential as a management tool but has yet to be evaluated in Lake Sturgeon. In spring 2009, six male and six female Lake Sturgeon in prespawn condition were captured using gill nets downstream of the Seven Sisters Generating Station, located on the Winnipeg River, Manitoba. Each fish received an acoustic transmitter and was released ∼ 500 m upstream of the station. Four stationary receivers were deployed in the 41-km stretch of river between the Seven Sisters and Slave Falls generating stations to monitor upstream movements, while an additional four were deployed downstream of Seven Sisters to monitor potential fallback. Following trap-and-transport, all 11 detected fish were observed moving rapidly upstream through backwatered habitats, into the stretch of river where Lake Sturgeon spawning sites occur, before or coincident with the onset of the spawning period. No fallback was observed during initial ascents. While further research is required, trap-and-transport of Lake Sturgeon may be a useful tool for fisheries managers wishing to facilitate historical spawning migrations interrupted by dams. Received February 18, 2013; accepted July 24, 2013
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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) | 0.002 | 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".