Impact of rainbow smelt (<i>Osmerus mordax</i>) invasion on walleye (<i>Sander vitreus</i>) recruitment in Wisconsin lakes
Bibliographic record
Abstract
Rainbow smelt (Osmerus mordax) are invaders of inland lakes in the Laurentian Great Lakes region of North America and have negatively affected native fish populations. Walleye (Sander vitreus) comprise an important fishery throughout the Great Lakes region and could be affected by rainbow smelt invasions. We test for declines of young-of-the-year walleye (YOY-W) density in 12 of the 26 known rainbow smelt invaded lakes in Wisconsin. Invaded lakes showed significantly lower YOY-W densities than uninvaded lakes during the period 1985–2004. In 94% (17/18) of years, YOY-W densities from invaded lakes were lower than those from uninvaded lakes. Declines (~70%) in YOY-W densities were observed in three lakes with data from before and after rainbow smelt invasion. For 10 invaded lakes with more than two YOY-W density estimates between 1985 and 2004, YOY-W densities averaged 13% below expected densities. Our results demonstrate the potential impacts of rainbow smelt invasion on walleye tribal, commercial, and recreational fisheries and highlight the importance of preventing their further spread.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".