Lake Sturgeon Geographic Range, Distribution, and Migration Patterns in the Saskatchewan River
Bibliographic record
Abstract
Abstract We examined geographic range, distribution, and migration patterns of Lake Sturgeon Acipenser fulvescens within the largest contiguous section of the Saskatchewan River system in Saskatchewan, Canada. Lake Sturgeon use portions of the North, South, and main‐stem Saskatchewan River during the summer months. The Forks area was observed to be an overwintering area. Lake Sturgeon were observed to migrate each year, and all Lake Sturgeon migrated at least once in the 3‐year study. Lake Sturgeon were observed to undertake significant migrations (>100 km/year) using all three rivers. Migration initiation date was consistent over the 3‐year period, whereas migration return date was more variable and may be linked to river flow rate. No significant differences in distance covered between years were identified, but Lake Sturgeon tended to migrate longer distances in years when flow rates were higher. Finally, the spatial extent of Lake Sturgeon in the Saskatchewan River System appears to be larger than that of many previously studied river and lake populations. This study provides important insights into Lake Sturgeon distribution and migration patterns within large prairie rivers, increasing our basic knowledge of this unique fish species in understudied river systems, and provides important information for conservation within their historic range. Received January 16, 2014; accepted August 5, 2014
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".