Geographical Variation In Songs of A Suboscine Passerine, the Alder Flycatcher ( <i>Empidonax alnorum</i> )
Bibliographic record
Abstract
Although there is a large body of literature dealing with the nature of geographic variation in the songs of birds, few studies have examined such variation across the entire range of species of suboscine birds. We measured time and frequency characteristics of songs of Alder Flycatchers (Empidonax alnorum) from six regions spanning almost the entire range of the species, from Alaska to Maine. Both univariate and multivariate analyses demonstrated significant differences in song characteristics among regions, and discriminant function analysis classified 69% of songs to the correct region. We found no relationship between geographic separation and magnitude of difference in songs among regions—songs of birds from some widely-separated regions were more similar than they were to songs of birds from neighboring regions. We argue that these regional differences have a genetic basis, but the pattern of variation does not appear to be consistent with a simple “isolation by distance” model. The variation may reflect differing adaptation to optimize acoustic transmission in varying habitats across the range. However, more detailed studies, including examination of genetic variation among populations, are required to test such suggestions rigorously.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".