Using Otolith Microstructure to Determine Natal Origin of Lake Ontario Chinook Salmon
Bibliographic record
Abstract
Abstract Stocking of hatchery-reared Chinook salmon Oncorhynchus tshawytscha in Lake Ontario has led to the development of a sport fishery that provides high economic returns to local communities. However, increased natural or “wild” production resulting from the naturalization of hatchery Chinook salmon to the system could result in changing salmonine dynamics that would require alteration of management practices in Lake Ontario. Using young-of-the-year (age-0) Chinook salmon of known origin—from hatchery and wild sources—we established a baseline for separating these two groups using otolith microstructure. Hatchery-reared Chinook salmon hatch earlier than wild Chinook salmon, and back-calculated hatch dates from otoliths correctly classified 97% of fish of known origin. A second protocol developed for determining the origin of Chinook salmon used the daily growth characteristics in the vicinity of 300 μm from the center of the otolith. Measuring the width of 20-d growth from 300 μm inward toward the origin correctly classified 100% of known hatchery fish and 89% of known wild fish. These measurements were used to determine the origin of Chinook salmon smolts caught in the nearshore of Lake Ontario adjacent to the Salmon River, New York, in 2000 and 2001. In both years, the nearshore population was dominated by naturally produced fish (85% to 89%). These results indicate that natural reproduction of Chinook salmon may play a larger role in Lake Ontario than previously thought.
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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 | 0.001 | 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".