How hollow melanosomes affect iridescent colour production in birds
Bibliographic record
Abstract
Developmental constraints and trade-offs can limit diversity, but organisms have repeatedly evolved morphological innovations that overcome these limits by expanding the range and functionality of traits. Iridescent colours in birds are commonly produced by melanin-containing organelles (melanosomes) organized into nanostructured arrays within feather barbules. Variation in array type (e.g. multilayers and photonic crystals, PCs) is known to have remarkable effects on plumage colour, but the optical consequences of variation in melanosome shape remain poorly understood. Here, we used a combination of spectrophotometric, experimental and theoretical methods to test how melanosome hollowness--a morphological innovation largely restricted to birds--affects feather colour. Optical analyses of hexagonal close-packed arrays of hollow melanosomes in two species, wild turkeys (Meleagris gallopavo) and violet-backed starlings (Cinnyricinclus leucogaster), indicated that they function as two-dimensional PCs. Incorporation of a larger dataset and optical modelling showed that, compared with solid melanosomes, hollow melanosomes allow birds to produce distinct colours with the same energetically favourable, close-packed configurations. These data suggest that a morphological novelty has, at least in part, allowed birds to achieve their vast morphological and colour diversity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".