The path toward consistent achievement of sea lamprey abundance and lake trout marking targets in Lake Ontario, 2000–2019
Bibliographic record
Abstract
Lake Ontario boasts a diverse fish community comprised of native and introduced species that support vibrant recreational, commercial and Indigenous fisheries. The effective delivery of a program to assess and control the sea lamprey (Petromyzon marinus) is crucial to achievement of Lake Ontario Fish Community Objectives of rehabilitating native fish stocks while protecting and maintaining the abundance of introduced salmonines. During 2000–2019, the Great Lakes Fishery Commission (GLFC) and its control agents, Fisheries and Oceans Canada (DFO) and the U. S. Fish and Wildlife Service (USFWS), delivered a consistent program of sea lamprey assessment and control. Beginning in 2004, rising sea lamprey abundance and marking rates on lake trout (Salvelinus namaycush) in Lake Ontario coincided with a decline of large lake trout in gillnet surveys. Efforts were undertaken to identify and control important sources of juvenile sea lampreys, including larvae that survived treatment, inhabited deepwater areas, or colonised previously uninhabited stream reaches and tributaries. A renewed reliance on proven conventional controls, including lampricide treatments and barriers, has resulted in consistent suppression of sea lamprey abundance and lake trout marking to prescribed targets in Lake Ontario during 2014–2019. This achievement is unprecedented in the 49-year history of Sea Lamprey Control Program delivery in Lake Ontario, and is attributable to the collaborative efforts of the GLFC, the control agents, and federal, provincial, state, and Indigenous partners.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".