Species Differences in the Songs of the Critically Endangered Niceforo's Wren and the Related Rufous-and-White Wren
Bibliographic record
Abstract
Abstract Niceforo's Wrens (Thryothorus nicefori) and Rufous-and-white Wrens (Thryothorus rufalbus) are closely related Neotropical birds. Niceforo's Wrens, critically endangered endemic Colombian songbirds, are generally considered a sister species to Rufous-and-white Wrens, although some have suggested that they may represent a well-marked race. A careful comparison of the two taxa has never been conducted. Here we present a thorough study of the songs of male Niceforo's and Rufous-and-white Wrens based on recordings collected throughout both species' geographic ranges. Both species sing low-pitched songs composed of varied pure tone whistles. Niceforo's Wren songs are shorter and simpler with fewer syllables and syllable types; they have higher frequency trills and terminal syllables; and they have distinctive terminal syllables with a broader bandwidth, higher frequency of maximum amplitude, and a larger number of frequency modulations. Discriminant analysis based on fine structural details of songs differentiates the two species. In a subspecies-level discriminant analysis, all five subspecies of Rufous-and-white Wren cluster together and are distinct from Niceforo's Wren. Comparisons of morphometric measurements and plumage features reveal parallel differences in body size (Niceforo's Wrens are larger for most measurements) and plumage color (Niceforo's Wrens are more gray than Rufous-and-white Wrens). This study is the first to compare Rufous-and-white versus Niceforo's Wrens with a quantitative approach and supports the idea that these taxa are best understood as distinct species.
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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 | 0.000 |
| 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) | 0.002 | 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".