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Record W4414894044 · doi:10.70747/cr.v4i3.529

Vestibulopatía Asociada a Hemoparasitosis en un Canino. Reporte de Caso

2025· article· es· W4414894044 on OpenAlexaboutno aff
Geovanny Patricio Bermeo Guerrero

Bibliographic record

VenueCiencia y reflexión : · 2025
Typearticle
Languagees
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsnot available
Fundersnot available
KeywordsEhrlichiaCoronavirus disease 2019 (COVID-19)Protozoal disease

Abstract

fetched live from OpenAlex

Este estudio de caso aborda la patogenia de los hemoparásitos en el sistema nervioso canino; integrando literatura científica reciente sobre prevención, ante el riesgo de convertirse en un problema de zoonosis. El objetivo: analizar la presencia de hemoparásitos (Ehrlichia canis, Babesia spp., Anaplasma spp.) en los caninos que manifiestan lesiones vestibulares, para que se logre el pronóstico y manejo clínico de estos animales mediante estrategias diagnósticas y terapéuticas. El método: tipo de estudio observacional, transversal y analítico, mediante la valoración entre hemoparasitosis y la manifestación de signos vestibulares; a través de: descripción del caso clínico del paciente canino identificado como un Labrador, jubilado de una unidad antinarcóticos. Se realizó: pre diagnóstico, exámenes complementarios y diagnóstico definitivo. Resultado: la infección por hemoparásitos se debió a la presencia de Ehrlichia canis, por lo cual presentó una lesión vestibular con síntomas (nistagmo, ataxia). En conclusión, la hemoparasitosis tiene impacto fuerte en el pronóstico y manejo clínico del animal afectado; se excluye el análisis de casos con historial de enfermedades neurológicas no relacionadas con hemoparásitos u otras causas; la enfermedad se presenta indistintamente en caninos de diferentes edades, sexo, raza, condición física general.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.302
Teacher spread0.294 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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