Evidence for resource polymorphism in the lake charr (<i>Salvelinus namaycush</i>) population of Great Bear Lake, Northwest Territories, Canada
Bibliographic record
Abstract
We sampled lake charr, Salvelinus namaycush, from Great Bear Lake, Northwest Territories, Canada, from June 30 to August 28, 2000. We assessed morphological variation in relation to stomach contents, age, and growth history of individual fish. We found significant differences in the morphology of insect-eating lake charr and fish-eating lake charr, specifically upper and lower jaw length, pectoral fin length, and caudal-peduncle depth. The age at capture did not vary between feeding types. However, otolith increment-width differences in the first 19 y of life were highly significant between feeding types. These results suggest that piscivorous lake charr grew faster than did insectivores. Our results support the hypothesis of trophic polymorphism in the lake charr in Great Bear Lake.
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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 | 0.001 | 0.001 |
| 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".