Retrospectively analysing condition in historical samples of birds
Bibliographic record
Abstract
Abstract Large amounts of nitrogen are used as fertilizer across the globe annually exceeding 100 million metric tons, with consequences for primary productivity and effects at higher trophic levels. We measured δ15N values in feathers from samples of eidersSomateria mollissimawintering on the Danish coast in 2014‐2016 and a century ago, using museum specimens. Blue musselsMytilus edulisare filter feeders relying on phytoplankton as food and they constitute the main diet of eiders. Feather δ15N increased by 40% during the past century reflecting increased terrestrial runoff of N through agricultural use of fertilizer, in turn supporting increased primary production in shallow coastal systems. This increase in δ15N was associated with an increase in body mass and longer duration of moult. However, there was a recent decrease in the quality of feathers as reflected by more fault bars and a higher degree of feather wear suggesting that longer duration of moult comes at a cost in terms of poorer feather quality. These findings imply that terrestrial nitrogen subsidies to coastal marine systems from anthropogenic sources has profound effects on species such as the eider as revealed by the effects on body condition and plumage quality and hence the ability to fly and dive.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".