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Record W4387321903

Seroprevalence immunodeficiency virus and feline leukemia in cats in Monteria, Córdoba SEROPREVALENCIA DEL VIRUS DE LEUCEMIA E INMUNODEFICIENCIA FELINA EN GATOS DE MONTERÍA, CÓRDOBA

2009· article· en· W4387321903 on OpenAlexaboutno aff
Ríos Rincón Rodrigo Alexander, Álvarez Arrieta Leonardo, Sánchez García Alba Eugenia, Tique Salleg Vaneza Paulin, Mattar Velilla Salim

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsCATSVirologyFeline immunodeficiency virusSeroprevalenceMedicineFeline leukemia virusLeukemiaVirusAntibodyViral diseaseImmunologySerologyLentivirusInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

The gradual increment of the feline population in Colombia and some countries is associated with presence of diseases that care produce animal health risk. The virus of immunodeficiency and the feline leukemia are the main retroviales diseases with high morbility and mortality in felines and they require of a right diagnostic that extend the felines’ life. A descriptive transversal cut study was done, 60 urban domestic cats of Montería were included, animals were from clinics, veterinarian consults and familiar houses. The simultaneous diagnostic of leukemia and feline immunodeficiency was carried out by using inmunoensayo SNAP combo FeLV Ag/FIV Ab (laboratories Idexx Toronto, Canadá) in samples of serum and plasma. The animals were submitted to a physical and laboratory examination the population studied were 30 females and 30 males most of them minor of 2 years. Feline leukemia showed a seroprevalence of 23,3% (14/60), for feline immunodeficiency a seroprevalence of 1,6% (1/60), and the prevalence of double infection for feline leukemia and immunodeficiency was of 5% (3/60). The immunodeficiency’s virus and feline leukemia diagnostic was carry out for first time in the population of domestics cats in the city of Montería and it established a seroprevalence of 23,3% and 1,6% respectively. El incremento gradual de la población felina en Colombia y algunos países está acompañado de la aparición de enfermedades que ponen en riesgo la salud animal. El virus de inmunodeficiencia y la leucemia felina son las principales enfermedades retrovirales de mayor morbilidad y mortalidad en los felinos, que requieren de un diagnóstico oportuno que permita prolongar la vida de estos animales. Se realizó un estudio descriptivo de corte transversal que incluyó 60 gatos domésticos del área urbana de la ciudad de Montería procedentes de clínicas, consultorios veterinarios y viviendas familiares. El diagnóstico simultáneo de leucemia e inmunodeficiencia felina se realizó en muestras de suero y plasma por el inmunoensayo comercial SNAP combo FeLV Ag/ FIV Ab (Laboratories Idexx Toronto, Canadá). Los animales fueron sometidos a exámenes físicos y de laboratorio. La población estuvo conformada por 30 hembras y 30 machos en su mayoría menores de dos años. La seroprevalencia fue del 23,3% (14/60) para leucemia felina, inmunodeficiencia felina 1,6% (1/60) y la seroprevalencia de doble infección por el virus de leucemia e inmunodeficiencia felina fue del 5% (3/60). Se realizó por primera vez el serodiagnóstico del virus de inmunodeficiencia y leucemia felina en la población de gatos domésticos de la ciudad de Montería; se estableció una seroprevalencia del 23,3% y 1,6% respectivamente.

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 score0.083
Threshold uncertainty score0.164

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 studies0.0010.000
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 head0.096
GPT teacher head0.498
Teacher spread0.402 · 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

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