An inventory of online reptile images
Bibliographic record
Abstract
No central online repository exists for the collection of animal images; hence it remains unclear how extensively species have been illustrated in the published literature or online. Here we compiled a list of more than 8000 reptile species (out of 11,341) that have photos in one of six popular online repositories, namely iNaturalist (6,349 species), the Reptile Database (5,144), Flickr (4,386), CalPhotos (3,071), Wikimedia (2,952), and Herpmapper (2,571). These sites have compiled over one million reptile photos, with some species represented by tens of thousands of images. Despite the number of images, many species have only one or a few images. This suggests that a considerable fraction of morphological and geographic variation is under documented or difficult to access. We highlight prominent gaps in amphisbaenians, lizards, and snakes, with geographic hotspots for species without images in Central Africa, Pacific Islands, and the Andes Mountains. We present a list of ~3,000 species without photos in any of the six databases and ask the community to fill the gaps by depositing images on one of these sites (preferably with minimal copyright restrictions).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.026 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.021 |
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".