Hatching success of walleye embryos in relation to maternal and ova characteristics
Bibliographic record
Abstract
Abstract – Understanding how maternal and ova traits influence offspring quality is a key issue in both ecological research and fish culture. We examined the survival and size at hatch of walleye embryos in relation to a suite of maternal and ova traits in laboratory incubation trials involving two native walleye populations. Ova were analysed for size, lipid content, fatty acid composition, soluble protein content and size composition, and mineral (Ca, Co, Cu, Fe, Mg, Mn and Zn) content. Embryonic survival (egg hatching success) varied most consistently with respect to spawning date and maternal age. Embryonic survival increased with maternal age, but other indices of maternal health, such as condition (residual mass at length) or somatic lipid content, did not account for significant amounts of variation. Indices of ova total lipid content, fatty acid composition and mineral composition explained significant variation in embryonic survival not accounted for by maternal age and spawning date, whereas indices of protein content and composition generally explained less variance. Both larval mass and length at hatch were primarily determined by ovum size, but length at hatch was also related to some aspects of ova fatty acid and mineral composition.
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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".