Male Bias in the Song Control System despite Female Bias in Song Rate in Streak-Backed Orioles <i>(Icterus pustulatus)</i>
Bibliographic record
Abstract
The song control system is a group of discrete interconnected nuclei found in the brains of all songbirds (suborder Passeri). Previous studies have reported a positive relationship between sex differences in song nucleus volumes and sex differences in song behavior across numerous songbird species, with species exhibiting greater sex differences in behavior also exhibiting greater sex differences in the brain. This body of comparative research, however, has failed to incorporate data from a bird species in which females sing more than males. In this study, we examine song nucleus volumes in both sexes of the streak-backed oriole (Icterus pustulatus), a New World blackbird with a female bias in song rate and similar song complexity between the sexes. Results from this neuroanatomical analysis are contrary to what was to be expected from previous research: despite the female bias in song rate, males have a significantly larger HVC and area X song nucleus volumes. Specifically, male HVC was 75% larger than that of females, and male area X was 64% larger than that of females. There was no significant sex difference in the size of the nucleus robustus arcopallialis. The lack of a positive relationship between song nuclei and singing behavior in these orioles demonstrates that our current understanding of song modulation via the song control system may be overly reliant on basic measures such as total volumes.
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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".