A Comparison of the Origins of Yellow Rails (<i>Coturnicops noveboracensis</i>) Wintering in Oklahoma and Texas, USA
Bibliographic record
Abstract
Numbers, densities, and sex ratios of Yellow Rails (Coturnicops noveboracensis) wintering at Red Slough Wildlife Management Area in McCurtain County, Oklahoma, USA, were approximated and compared to estimates from birds wintering in coastal Texas, USA. Deuterium (δD) and sulfur (δ34S) values from rectrices of birds wintering in Oklahoma and in Texas were also examined to determine where the birds bred. Yellow Rails in Oklahoma from October 2009 through April 2010 were banded. Fifty-six Yellow Rails were captured, and the population was estimated to consist of 90.3 ± 25.5 birds, or 5.3 ± 1.5 rails * ha-1, which is similar to the published density of Yellow Rails in coastal Texas. Sex ratios did not differ from an expected 1:1 male:female ratio and did not differ between Oklahoma and Texas. Rectrices from Texas (n = 40) and Oklahoma (n = 32) had similar δD values and were broadly consistent with published δD values from southeastern Alberta to James Bay in Ontario and Quebec, Canada. The δ34S analysis from Texas (n = 4) and Oklahoma (n = 35) showed only two birds, both from Texas, with enriched δ34S values, suggesting that most birds from Texas and Oklahoma bred in interior Canadian marshes. Although the sample size was small, these results suggest interior overwintering sites contain similar densities to coastal 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 | 0.001 | 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".