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Record W2891651351 · doi:10.31533/pubvet.v12n9a178.1-7

Nefrectomia unilateral em um cão parasitado por Dioctophyma renale: relato de caso

2018· article· en· W2891651351 on OpenAlexaff
Dilma Mendes de Freitas, Bruna Piva Maria, Bárbara Michelle Araújo Vasconcelos, Ana Jorge, Ananda Neves Teodoro, Endrigo Gabellini Leonel Alves, Isabel Rodrigues Rosado

Bibliographic record

VenuePubVet · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicPaleopathology and ancient diseases
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsUrinalysisMedicineNephrectomyAbdominal ultrasonographyAbdominal painAsymptomaticSurgeryAbdominal ultrasoundUltrasonographyKidneyUrineInternal medicine

Abstract

fetched live from OpenAlex

Dioctophyma renale is a helminth that parasites the kidneys of dogs and whose infection is acquired by ingestion of larvae that may be present in fish, frogs or aqua annelids. The right kidney and abdominal cavity are the places where the parasite is most commonly found. The clinical signs in general are hematuria, inappetence and low back pain, however, the animals can be asymptomatic when only one kidney is parasitized. The diagnosis is made through ultrasonography, urinalysis and excretory urography and the treatment consists of nephrectomy for advanced cases or nephrectomy for removal of the parasite in cases with early diagnosis. The present study describes the case of a 2 year old bitch from a farm attended at the Veterinary Hospital of Uberaba and diagnosed with Dioctophyma renale by ultrasound and urinalysis. The treatment was done by unilateral nephrectomy with excelent postoperative recovery.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.249
Teacher spread0.225 · 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 designCase report
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

Citations5
Published2018
Admission routes1
Has abstractyes

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