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Síndrome da cauda flácida em cão da raça labrador retriever: primeiro relato no Brasil

2006· article· pt· W2049178546 on OpenAlexaboutno aff
Maria Lígia de Arruda Mistieri, Vera Grevel, João Guilherme Padilha Filho, Jõao Paulo da Exaltação Pascon, Júlio Carlos Canola, Daniel Orlato, Marileda Bonafim Carvalho

Bibliographic record

VenueCiência Rural · 2006
Typearticle
Languagept
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnatomyHumanitiesArt

Abstract

fetched live from OpenAlex

A síndrome da cauda flácida é uma enfermidade que acomete cães de caça, principalmente Labradores Retriever e do grupo Pointer. Embora sua etiologia não esteja totalmente definida, sabe-se que sua ocorrência é precedida de esforço físico extenuante, exposição ao frio ou água fria e confinamento em caixas de transporte. O presente trabalho descreve o caso de um cão da raça Labrador Retriever, macho não castrado, de quatro anos de idade que apresentou súbita dor e flacidez da cauda após banho frio. Fratura vertebral, síndrome da cauda eqüina, outras enfermidades da medula espinhal ou de glândulas adanais e afecções prostáticas foram descartadas após exames auxiliares. A divulgação deste relato é relevante uma vez que esta síndrome ainda não foi descrita no Brasil.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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