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Record W2809401851 · doi:10.1017/s0031182018000999

Nasal mites (Mesostigmata: Rhinonyssidae) in African penguins (<i>Spheniscus demersus</i>)

2018· article· en· W2809401851 on OpenAlexafffund
Ralph Eric Thijl Vanstreels, H. C. Proctor, Albert Snyman, Renata Hurtado, Katrin Ludynia, Nola J. Parsons, Pierre Pistorius

Bibliographic record

VenueParasitology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBird parasitology and diseases
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyMesostigmataObligateNasal cavityZoologyPygoscelisAnatomyAcariEcology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.005

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.

Opus teacher head0.012
GPT teacher head0.291
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2018
Admission routes2
Has abstractyes

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