Otolith-derived estimates of marine temperature use by West Greenland Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
Abstract Otolith-derived estimates of mean marine temperatures used by West Greenland 1SW Atlantic salmon (Salmo salar) of North American origin were determined for fish collected in 2009 and 2010. Otolith material corresponding to the second summer at sea was subsampled, via micro-milling, and analysed by mass spectrometry to produce stable oxygen isotope (δ18O) values from which temperature use estimates were obtained from a salmonid-based fractionation equation. Mean temperature estimates did not differ significantly by period (early vs. late summer), or capture year. The mean and variation estimates were also consistent with temperature use values previously published in the literature or derived from the limited number of data storage tags that have been retrieved for Atlantic salmon, with 80% of all individuals occupying temperatures in the 3.9–9.7°C range. Among-individual differences in temperature use did not correlate with measured otolith growth zone widths. Given the temporal, spatial and methodological variation associated with the derivation of marine temperature use estimates for Atlantic salmon, the data were interpreted to define a range of preferred temperatures within which among-individual differences in growth were driven by the interaction of feeding and temperature use, possibly as a result of the opportunistic feeding behaviour known to predominate among Atlantic salmon.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".