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Record W7120658647

Chagasic myocarditis in dogs in Rio Grande do Sul

2009· article· pt· W7120658647 on OpenAlexaboutno aff
Saulo Petinatti Pavarini, Eduardo Conceição de Oliveira, Paulo Mota Bandarra, Juliano S. Leal, Eufrosina Setsu Umezawa, Daniela Bernadete [UNESP] Rozza, David Driemeier

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2009
Typearticle
Languagept
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsnot available
Fundersnot available
KeywordsMyocarditisTrypanosoma cruziChagas diseaseSerologySudden deathAmastigote
DOInot available

Abstract

fetched live from OpenAlex

Acute Chagas disease caused sudden death in two dogs from Porto Alegre rural zone of, Rio Grande do Sul, southern Brazil. A 9-month-old Pit Bull male (dog 1) and a 2-year-old Labrador Retriever female (dog 2) died in January 2005 and May 2008, respectively. At necropsy, the hearts were enlarged. In dog 2, heart was remarkably globoid with multiple pale areas scattered in the myocardium, especially in the right ventricle. Heart chambers, especially in the right side, were dilated. Histological findings were similar in both cases and consisted of diffuse non suppurative myocarditis predominantly with lymphocytic interstitial infiltrates. Within myocardial fibers were observed pseudocysts filled with amastigotes forms of Trypanosoma cruzi. Serologic test TESA-blot resulted positive in samples from dog 2 and showed IgM e IgG anti-T.cruzi antibodies characteristic of acute Chagas disease. The results indicate that Trypanosoma cruzi infection must be considered in the differential diagnosis of sudden death in dogs in southern Brazil and that the specie may act as a reservoir and sentinel for the disease in human beings.

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 score0.008
Threshold uncertainty score0.016

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.025
GPT teacher head0.279
Teacher spread0.253 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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