Spatial and seasonal variation in diet, growth and condition of walleye (Sander vitreus), sauger (Sander canadensis) and dwarf walleye (Sander vitreus) in Lake Winnipeg, Manitoba
Bibliographic record
Abstract
Lake Winnipeg has the second largest walleye fishery in North America. The North and South Basins of the lake differ in many ways, e.g. water temperature, turbidity, and fish community. The study objectives were to determine if (a) growth, condition or diet of walleye, sauger or dwarf walleye differed between basins, (b) among seasons, and (c) whether the invasive rainbow smelt are associated with these differences. Walleye, sauger and dwarf walleye were caught using gill-nets and analysed for growth, condition and diet in all seasons. Walleye and sauger in the North Basin showed higher growth rates and condition than in the South Basin. Diet in the South Basin had more diverse species composition, whereas in the North Basin, the diet consisted almost entirely of rainbow smelt. Some seasonal variation was also documented and the impact of rainbow smelt seems to be positive for these piscivorous fish in Lake Winnipeg.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".