Detection of natural barriers to movement of lake sturgeon (Acipenser fulvescens) within the Namakan River, Ontario
Bibliographic record
Abstract
Many populations of lake sturgeon ( Acipenser fulvescens Rafinesque, 1817) are below historic population sizes, and migration barriers have likely contributed to some of these population declines. Dams and natural barriers can potentially isolate populations along a single river and can have a strong effect on the ability of lake sturgeon to move upstream. Along the Namakan River in Ontario, Canada, a series of natural rapids could impede movement of lake sturgeon and fragment the sturgeon into several small populations. Movement patterns of lake sturgeon were assessed using genetics and acoustic telemetry. Samples were collected from five locations along the river, each one separated by a rapid or falls, and were analyzed at 12 microsatellite loci. No significant genetic differences were observed between the five segments, indicating that the groups of lake sturgeon are not isolated. There were no significant differences in genetic diversity between the five segments. Therefore, migration is likely occurring both upstream and downstream. The acoustic telemetry study also confirmed bidirectional movement of adult fish. The natural rapids and falls along the Namakan River do not appear to be a significant barrier to movement of lake sturgeon, and the lake sturgeon within this river represent a single population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".