Muskellunge Management: Fifty Years of Cooperation Among Anglers, Scientists, and Fisheries Biologists
Bibliographic record
Abstract
Abstract.—The Muskellunge Esox masquinongy is native to Lake Simcoe, Ontario and historically supported commercial and sport fisheries. After significant overharvest, habitat loss, and ecological change in the late 1800s and early 1900s, the Lake Simcoe population was substantially reduced by the 1930s. Despite extensive stocking from the late 1930s through to the late 1960s, Muskellunge were rarely detected beyond the 1980s, although the sport fishery remained open until 2005. More recently, restoration feasibility and habitat inventory studies determined that restoration of the Lake Simcoe Muskellunge population is a realistic management objective. The goal of the Lake Simcoe Muskellunge Restoration Project is to restore a self-sustaining Muskellunge population to Lake Simcoe through a long-term collaborative effort that includes habitat enhancement, rehabilitative stocking, and effectiveness monitoring. Rehabilitative stocking was initiated in 2005 and habitat rehabilitation efforts focused on critical spawning and nursery areas. Here, we provide recent results from early effectiveness monitoring efforts and identify challenges related to restoring Muskellunge and their habitats. These and other obstacles are being addressed through the ongoing partnerships that have guided this long-term restoration project to date.
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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 | 0.009 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".