Ecological correlates of variable organ sizes and fat loads in the most northerly wintering shorebirds
Bibliographic record
Abstract
Shorebirds at northern latitudes during the nonbreeding season typically carry relatively large lipid stores and exhibit an up-regulation of lean tissues associated with digestion and thermogenesis. Intraspecific variation in these tissues across sites primarily reflects differences in environmental conditions. Rock (Calidris ptilocnemis (Coues, 1873)) and Purple (Calidris maritima (Brünnich, 1764)) sandpipers are closely related species having the most northerly nonbreeding distributions among shorebirds, living at latitudes up to 61°N in Cook Inlet, Alaska, and up to ∼71°N in northern Norway, respectively. Cook Inlet is the coldest known site used by nonbreeding shorebirds, and the region’s mudflats annually experience extensive coverage of foraging sites by sea and shore-fast ice. Accordingly, Rock Sandpipers increase their fat stores to nearly 20% of body mass during winter. In contrast, Purple Sandpipers exploit predictably ice-free rocky intertidal foraging sites and maintain low (<6.5%) fat stores. Rock Sandpipers increase the mass of lean tissues from fall to winter, including contour feathers, stomach, and liver components. They also have greater lean pectoralis and supracoracoideus muscle and liver and kidney tissues compared with Purple Sandpipers in winter. This demonstrates a combined emphasis on digestive processes and thermogenesis, whereas Purple Sandpipers primarily augment organs associated with digestive processes. The high winter fat loads and increased lean tissues of Rock Sandpipers in Cook Inlet reflect the region’s persistent cold and abundant but sporadically unavailable food resources.
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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 | 0.000 |
| 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 | 0.000 | 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".