Trophic ecology of Arctic char (Salvelinus alpinus L.) in the Cumberland Sound region of the Canadian Arctic
Bibliographic record
Abstract
Trophic ecology is a key component in describing patterns of variation between and within populations, particularly in Arctic marine systems wherein climate change is impacting food webs. This thesis investigates the trophic ecology of Arctic char (Salvelinus alpinus) in the Cumberland Sound region using a multi-indicator approach. My data show trophic niche differences between resident and anadromous ecotypes and evidence for estuarine feeding by residents. I document a shift in the marine diet of Arctic char from zooplankton to capelin (Mallotus villosus) – a novel prey species in this region – that has occurred in less than a decade. Changes in Arctic char growth imply population-level effects of this shift; however, more research is required. Finally, I find lipid effects on δ13C and lipid-extraction effects on δ15N and δ34S for Arctic char muscle tissue. Lipid-correction models did not provide adequate δ13C estimates; thus, chemical extraction or ecotype-specific validation of models is recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".