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Record W3163795111

CONSIDERACIONES ÉTICAS Y JURÍDICAS SOBRE BIENESTAR ANIMAL EN UNIDADES DE PRÁCTICA LABORAL INVESTIGATIVA / ETHICAL AND LEGAL CONSIDERATIONS ON WELFARE ANIMAL IN INVESTIGATIONAL LABOR PRACTICE UNITS

2020· article· es· W3163795111 on OpenAlexaboutno aff
Jorge Orlay Serrano Torres, Jessica Varela Torres

Bibliographic record

VenueUniversidad&Ciencia · 2020
Typearticle
Languagees
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

En el presente trabajo se realiza un analisis de las consideraciones eticas y juridicas sobre bienestar y experimentacion animal y se hace referencia a un folleto que reune la normativa al respecto, publicado como material de apoyo a la docencia. El estudio abarco un analisis donde se tomo como referencia el conjunto de leyes y regulaciones mas importantes puestas en vigor por los paises miembros de la Comunidad Europea, incluidas las nuevas legislaciones, uso de alternativas y el control sobre los procedimientos en los experimentos. Se incluyo tambien lo regulado en Canada y EE.UU. y al referirse a Cuba se explica lo hecho hasta el presente en materia de proteccion con respecto al uso de los animales a traves de las medidas dictadas por el Centro de Produccion de Animales de Laboratorio. En el caso de los animales productivos y utilizados en la docencia se trabajo sobre la base de lo estipulado en Leyes, Decretos-Leyes, Decretos, Resoluciones e Instrucciones del Comite Ejecutivo del Consejo de Ministros, el Ministerio de la Agricultura y el Instituto de Medicina Veterinaria. Finalmente, se establece un resumen del folleto que reune lo legislado en cuanto a proteccion animal, y de esta forma se orienta el trabajo diagnostico llevado a cabo por los estudiantes de las Ciencias Agropecuarias durante la practica laboral investigativa en la Empresa Agropecuaria Ruta Invasora.

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)0.001
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), 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 score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
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 head0.100
GPT teacher head0.364
Teacher spread0.263 · 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
Published2020
Admission routes1
Has abstractyes

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