Sea lamprey (<i>Petromyzon marinus</i>) size trends in a salmonid stocking context in Lake Superior
Bibliographic record
Abstract
Fish community objectives for Lake Superior call for restoration such that it resembles its historical species composition, to the extent possible, yet allow for supplementation of naturalized Pacific salmonids (Oncorhynchus spp.). To achieve these goals, managers strive to control the sea lamprey (Petromyzon marinus) to levels that cause insignificant (<5%) mortality to host species. While control efforts have been successful, sea lamprey size has increased during the control period. We analyzed long-term sea lamprey size trends and found a significant increase from 1961 to 2003 (F = 36.76, p < 0.001, R2 = 0.473). A local regression revealed two significant size increase periods. We used Bayesian model averaging to find the relationship between sea lamprey size and the stocking of salmonids (lean lake trout (Salvelinus namaycush) and Pacific salmon). Bayesian model averaging identified 91 models, and several regressors were common features in many of the models. Sea lamprey weight was related to stocked lake trout lagged 3, 9, 11, and 13 years, and stocked Pacific salmon lagged 4 years. If sea lampreys can achieve larger sizes attached to Pacific salmonid hosts, and thus inflict more damage, there may be a trade-off for managers in achieving the fish community objectives for Lake Superior.
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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".