Bibliographic record
Abstract
The Taylor White Collection of paintings from the 1700s, held at the McGill University Library, includes 661 paintings that illustrate 832 birds from around the world. With illustrations of 443 species in 30 avian orders, this collection represents a substantial proportion of the bird species known at the time and is one of the most comprehensive and accurate collections of coloured bird illustrations made during the eighteenth century. Most of the paintings were made by Charles Collins and Peter Paillou from live birds or dead specimens in the cabinets and aviaries of White and his contemporaries. We compared a large sample of the paintings with the same birds depicted in modern bird guides to assess quantitatively the accuracy of the illustrations with respect to the colours and patterns of plumages and soft parts. We found that fewer than 3% of the paintings contained errors, and usually only in one of the 28 body regions that we assessed. Given this high level of accuracy, we identified a small red macaw from the West Indies as likely representing a previously unknown but now extinct subspecies of the Scarlet Macaw, and two other paintings of species that could not be convincingly matched to any known species.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".