Genetic divergence and connectivity among river and reef spawning groups of walleye (<i>Sander vitreus vitreus</i>) in Lake Erie
Bibliographic record
Abstract
Discerning population genetic structure is challenging for highly vagile open water animals, as contemporary gene flow may obscure historic phylogeographic patterns. We examined genetic variation among all 10 major river and reef spawning groups of walleye (Sander vitreus vitreus) in Lake Erie for evidence of isolation by distance, segregation by physiographic partitions, and natal site fidelity using 10 nuclear DNA microsatellite loci. Results revealed that although most spawning groups were distinguishable, relationships did not correspond with physiographic basins or distances among localities. Bayesian analyses showed connectivity among some southern shore spawning groups, which included the largest-sized groups. Significant genetic divergence was discerned among walleye spawning in the river systems of eastern Lake Erie, as well as in two sites in western Lake Erie, along with marked isolation from Lake St. Clair. Population structure of Lake Erie walleye thus appears to reflect the interaction of two different intrinsic factors: isolation due to natal site fidelity that maintains patterns of divergence, and connectivity due to individuals that stray from their natal sites to spawn.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".