Contrasting strategies of ova lipid provisioning in relation to maternal characteristics in three walleye (<i>Sander vitreus</i>) populations
Bibliographic record
Abstract
We examined how the lipid content and fatty acid composition of walleye (Sander vitreus) ova varied with respect to maternal characteristics, particularly indices of body nutrient reserves, within three spawning populations that varied in maternal age, size, and somatic lipid reserves. We also compared the variability in ova lipid composition among three populations with that observed among spawning years within one of these populations. Maternal characteristics had little influence on ova lipid content. In Lake Ontario, percentages of docosahexaenoic acid (22:6(n-3), DHA) and arachidonic acid (20:4(n-6), AA) increased with maternal length, while those of eicosapentaenoic acid (20:5(n-3), EPA) declined. In Lake Nipissing, maternal age had similar effects on AA and EPA, but not DHA. The Lake Winnipeg population did not conform to the trends of the other two populations, and ova from this population had very low levels of AA. We hypothesize that there are similar selection pressures on the Lake Ontario and Lake Nipissing populations with respect to desirable ova fatty acid profiles. Lake Winnipeg walleye may experience different selection pressures or may be unable to conform to the trends observed in the other two lakes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".