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Morphological variability and genetic identity in <i>Rhinoestrus</i> spp. causing horse nasal myiasis

2005· article· en· W2115324745 on OpenAlexaff
Domenico Otranto, Piermarino Milillo, Donato Traversa, Douglas D. Colwell

Bibliographic record

VenueMedical and Veterinary Entomology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyIntraspecific competitionZoologyTaxonMyiasisLarvaRibosomal RNA16S ribosomal RNAMitochondrial DNARibosomal DNAPhylogeneticsGeneGeneticsEcology

Abstract

fetched live from OpenAlex

Larvae of Rhinoestrus purpureus (Brauer) and Rhinoestrus usbekistanicus Gan (Diptera: Oestridae) cause nasal myiases of equids. During a recent epidemiological survey in southern Italy some morphological and taxonomical doubts arose concerning the identification of Rhinoestrus third stage larvae on the basis of the features of the posterior spiracles and the distribution of dorsal spines on the third segment. Four different morphotypes were retrieved: R. usbekistanicus-like, R. purpureus-like and two morphotypes with shared features. The genes encoding for the mitochondrial cytochrome oxidase I (COI) and for the ribosomal subunits 16S and 28S of the four morphotypes of Rhinoestrus were investigated to determine whether they belonged to a single taxon or they displayed genetic differences indicative of more than one species. The three genes showed a very low level of sequence variation (COI 0-0.43%, 16S 0-1.45%, 28S 0-0.23%) falling within the intraspecific ranges previously described for Oestridae species. Finally, the peritreme features and the spinulation of the third segment of the four morphotypes examined could not be used to differentiate the two 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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.276
Teacher spread0.252 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2005
Admission routes1
Has abstractyes

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