Geographic variation in the isotopic (δD, δ<sup>13</sup>C, δ<sup>15</sup>N, δ<sup>34</sup>S) composition of feathers and claws from lesser scaup and northern pintail: implications for studies of migratory connectivity
Bibliographic record
Abstract
Stable hydrogen isotope (δD) measurements of bird feathers can reveal approximate North American latitudes where feathers were grown by linking feather δD values to well-defined geographic patterns in δD values in growing-season precipitation. In waterfowl, this approach may require caution because wetlands are potentially “disconnected” from predictable isotopic patterns in precipitation waters. Stable carbon (δ13C), nitrogen (δ15N), and sulphur (δ34S) isotope values of avian tissues may show geographic structure but can be complicated by land use. We analyzed claws of wintering adult northern pintails (Anas acuta L., 1758) from California and Texas, and feathers and claws of lesser scaup ( Aythya affinis (Eyton, 1838)) ducklings from northwestern North America, to determine geographic variation in δD, δ13C, δ15N, and δ34S values. Wintering pintails from Texas and California were distinguished with claw δD and δ15N values. In scaup, feather δD values differed among biomes and were positively associated with latitude; geographic variation in other isotopes was less pronounced. The δD values in feathers and claws of individual scaup ducklings were correlated. A positive relationship between scaup feather δD values and δD values in growing-season precipitation was similar to results reported for songbirds. Thus, δD values in waterfowl feathers can provide new knowledge about natal origins and moulting sites.
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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 | 0.001 | 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".