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Endoparasitoses de equinos no município de Camaquã, RS, Brasil

2020· article· pt· W3033852352 on OpenAlexaff
Mary Jane Tweedie de Mattos, Rodrigo Arioli, Sandra Márcia Tietz Marques

Bibliographic record

VenueRevista Agraria Academica · 2020
Typearticle
Languagept
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsVeterinary medicineHelminthsBiologyDiarrheaHelminthiasisLarvaMedicineZoologyEcologyGastroenterology

Abstract

fetched live from OpenAlex

As helmintoses em equinos podem causar enterite levando a quadros de diarréia.O objetivo deste estudo foi identificar e quantificar os helmintos predominantes em equinos mantidos em criações extensivas no município de Camaquã, RS.Amostras fecais de 67 equinos foram processadas pelos Métodos de Gordon; Whitlock modificado e Roberts; Sullivan.Das amostras coletadas observou-se que 94,02% (63/67) apresentavam ovos de Strongylida, sendo que 49,25% apresentavam OPG de Strongylida acima de 1001.A coprocultura revelou que 90% das larvas eram de Cyclocyclus e 10% de Gyalocephalus considerados como ciastomíneos.Estes resultados demonstram a necessidade de maior controle parasitário em equinos que tenham contato direto com larvas infectantes dos helmintos em criações extensivas.

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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
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 head0.062
GPT teacher head0.330
Teacher spread0.268 · 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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