Patterns of vocal divergence in a group of non-oscine birds (auklets; Alcidae, Charadriiformes)
Bibliographic record
Abstract
Question: Are phylogenetic relationships the major determinant of vocal relationships in non-oscine birds (birds that do not have a learning component in the vocalization)? Background: Both environmental variables and phylogenetic affinities can affect vocalizations. Unlearned vocalizations are characteristics of most non-oscine bird families, which have a relatively less-complex syrinx and vocalizations. Organism: A monophyletic group of underground-nesting seabirds (auklets: Aethiini, Alcidae, Charadriiformes) from the Aleutian Islands, Alaska, USA. Methods: We mapped vocal characters (28 acoustic and 10 syringeal) from total repertoires of all members of the tribe Aethiini onto a molecular phylogeny to compare the relative influence of phylogeny and breeding habitat on vocal divergence. Conclusion: Phylogeny, visual display, and ecological factors have contributed to vocal divergence in this clade. Temporal attributes and syringeal attributes of the acoustics of vocalization showed high congruence with phylogeny. Frequency attributes, which are affected by environmental variables, showed low congruence, and therefore high homoplasy.
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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 | 0.001 |
| 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) | 0.001 | 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".