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Record W3048547599 · doi:10.1177/0300985820948819

Algal Lymphadenitis in a Dog Caused by <i>Scenedesmus</i> Species

2020· article· en· W3048547599 on OpenAlexaboutno aff
Ryan D. Oliveira, Rebecca Wolking, Daniel S. Bradway, Trevor L. Alexander, Claire R. Burbick, Ilaria Cerchiaro, Chrissy Eckstrand

Bibliographic record

VenueVeterinary Pathology · 2020
Typearticle
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsBiologyLymph nodePathologyScenedesmusLymphInternal transcribed spacerAlgaeRibosomal RNAAnatomyMicrobiologyBotanyMedicineGeneImmunology

Abstract

fetched live from OpenAlex

A 6-year-old, spayed female Labrador/Weimaraner cross-breed dog that had previously lived in Arizona presented in Montana for an annual examination with an incidentally enlarged popliteal lymph node, which was subsequently biopsied. Histologically, the lymph node was expanded by eosinophil-rich granulomas with both extracellular and intrahistiocytic green algae. These algae had intracytoplasmic, birefringent, and refractile granules; readily formed 2 to 3 mm green colonies on Columbia blood agar medium; and ultrastructurally had a multilayered cell wall and intracytoplasmic chloroplasts. Amplified product from the internal transcribed spacer and D1/D2 regions of the 28S ribosomal RNA gene had high sequence identity to Scenedesmus sp. Despite similar infection in the retropharyngeal lymph node 1 year later, the animal remained otherwise healthy with no clinical signs. To the authors’ knowledge, this is the first case of Scenedesmus species infection in a dog and is a differential diagnosis for Coccidioides immitis.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.051
GPT teacher head0.286
Teacher spread0.235 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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