Influences of female body condition on recruitment success of walleye (<i>Sander vitreus</i>) in Wisconsin lakes
Bibliographic record
Abstract
Stock reproductive potential informs population dynamics and response to harvest. Indices of body condition, like relative weight (Wr), may indicate individual energetic state and provide a mechanistic link between spawning stock traits and recruitment. We tested for relationships among Wr of three female size classes (381–456, 457–557, and ≥558 mm total length), reproductive traits, and age-0 recruitment using data from 92 walleye (Sander vitreus) populations in the Ceded Territory of Wisconsin during 1989–2015 and a lake-specific time series from Escanaba Lake, Wisconsin, during 1958–2014. In Escanaba Lake, Wr was positively related to maturation in small females and was positively related to fecundity and gonadosomatic index in intermediate fish. Among and within populations, Wr demonstrated compensatory density dependence and positive relationships with growing degree-days. Recruitment was positively related to large female Wr variation across lakes and negatively related to small female Wr variation in Escanaba Lake. Improving the condition of large female walleye may promote recruitment, and Wr may serve as an accessible metric of reproductive potential in walleye stock–recruit analyses.
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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 | 0.000 | 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".