Nasal mites (Mesostigmata: Rhinonyssidae) in African penguins (<i>Spheniscus demersus</i>)
Bibliographic record
Abstract
Rhinonyssids are obligate haematophagous mites that parasitize the nasal cavity of vertebrates, and occur in a wide range of birds worldwide. Two species of nasal mites are known to occur in penguins: Rhinonyssus sphenisci, which has been recorded from Humboldt and Magellanic penguins (Spheniscus humboldti and S. magellanicus, respectively), and Rhinonyssus schelli, which has been recorded in Adélie and Gentoo penguins (Pygoscelis adeliae and P. papua, respectively). We examined the nasal cavity of African penguins (Spheniscus demersus) that died while under care at a rehabilitation centre (N = 40) or that were found dead at breeding colonies (N = 67). Nasal mites were found in the nasal cavity and/or paranasal of sinuses of 21 penguins, some of which had signs of mild-to-moderate sinusitis. Prevalence was higher in juveniles (29%) and adults (27%) than in chicks (10%). Mean intensity was 5.9 ± 12.9 mites per infected host (range 1-60). The mites presented morphological characteristics that were at times consistent with either R. sphenisci or R. schelli, and therefore we conservatively classified them as 'R. sphenisci sensu lato'. Our morphometric results raise the question of whether the specific status of R. schelli is justified.
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 | 0.000 |
| 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 | 0.001 |
| 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".