High prevalence of basin fidelity and homing by lake trout (<i>Salvelinus namaycush</i>) in a small northern lake
Bibliographic record
Abstract
Identifying how habitat structure influences the spatiotemporal movements of fishes is important for conservation, population assessment, and management purposes. Here, we determined whether acoustically tagged lake trout (Salvelinus namaycush) from a 305 ha lake exhibited homing behaviour and lake basin fidelity over multiple seasons and years. The lake has two distinct deep basins (north and south) connected by a shallower centre basin. Fifteen lake trout captured during the spawning season from both deep basins were tagged and released in the south basin. All translocated north-basin fish quickly returned to the north basin (median = 1.85 days, range = 0.36–4.5 days), apart from one fish that returned 41 days post-release, while none from the south ventured into the north basin during this time. After translocated individuals returned, all fish demonstrated high basin fidelity among years, as >90% of detections were from the same basin fish were captured, while <0.7% (by three fish) were from the opposite deep basin and <9% from the centre basin. The probability a fish was detected outside its basin of capture was highest in winter (15.9%) and fall (14.3%) and lowest in summer (0.41%).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".