Variation in colour within a population of northern flickers: a new perspective on an old hybrid zone
Bibliographic record
Abstract
We used a digital camera to quantify the colour of the tail feathers of 245 northern flickers (Colaptes auratus) in central British Columbia and investigate the frequency of colour morphs in the population of hybrids. The colour values generated by the camera corresponded well to the conventional method of ranking colours by eye, but was advantageous because it provided finer discrimination and a continuous colour variable. Rectrix colour varied in a continuum from the yellow of C. a. auratus to the red of C. a. cafer. By experimentally exposing red and yellow feathers to sunlight we showed that the intermediate orange colours were not a result of secondary fading of the carotenoid pigments. The distribution of colours in the population was bimodal. A paucity of intermediate phenotypes (orange birds) could not be explained by their mortality because return rates of birds to our study area was not associated with colour. New immigrants into the population tended to resemble parental types more often than hybrids. Assortative mating by colour in this population may tend to keep the subspecies separate, contrary to the situation in more southerly areas of the hybrid zone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".