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Record W7015333263

Seroprevalencia del virus de leucemia e inmunodeficiencia felina engatos de Monteria Cordoba

2009· article· es· W7015333263 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2009
Typearticle
Languagees
FieldSocial Sciences
TopicAnimal Law and Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationVirusHuman immunodeficiency virus (HIV)Nutritionist
DOInot available

Abstract

fetched live from OpenAlex

El incremento gradual de la poblacion felina en Colombia y algunos paises esta acompanado de la aparicion 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 diagnostico oportuno que permita prolongar la vida de estos animales Se realizo un estudio descriptivo de corte transversal que incluyo 60 gatos domesticos del area urbana de la ciudad de Monteria procedentes de clinicas consultorios veterinarios y viviendas familiares El diagnostico simultaneo de leucemia e inmunodeficiencia felina se realizo en muestras de suero y plasma por el inmunoensayo comercial SNAP combo FeLV Ag FIV Ab Laboratories Idexx Toronto Canada Los animales fueron sometidos a examenes fisicos y de laboratorio La poblacion estuvo conformada por 30 hembras y 30 machos en su mayoria menores de dos anos La seroprevalencia fue del 233 1460 para leucemia felina inmunodeficiencia felina 16 160 y la seroprevalencia de doble infeccion por el virus de leucemia e inmunodeficiencia felina fue del 5 360 Se realizo por primera vez el serodiagnostico del virus de inmunodeficiencia y leucemia felina en la poblacion de gatos domesticos de la ciudad de Monteria se establecio una seroprevalencia del 233 y 16 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 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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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 designTheoretical or conceptual
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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