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Record W944374004

Animal use control in teaching and research.

2010· article· en· W944374004 on OpenAlexaboutno aff
Vanessa Carli Bones, Elaine Cristina de Oliveira Sans, Ralf-Peter Simon, Carla Forte Maiolino Molento

Bibliographic record

VenueArchives of Veterinary Science · 2010
Typearticle
Languageen
FieldVeterinary
TopicAnimal testing and alternatives
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryDecreeLegislationAnimal welfareParliamentPolitical sciencePublic administrationAgricultureWelfareLawGeographyPolitics
DOInot available

Abstract

fetched live from OpenAlex

The animal experimentation regulation is based on the ethical concern regarding not to cause animal suffering, expressed by social movements in favour of the animal protection, legislation on this subject, Animal Use Ethics Committees, amongst others. The objective of this review was to study the control of animal use in teaching and research in some countries, randomly selected, comparing them to the situation in Brazil and the State of Parana. The control process is performed by different institutions in different countries: the President and Parliament in South Africa; autonomous institution in Canada; Department of Agriculture in United States; Ministry of Education, Culture, Sports, Science and Technology in Japan; Federal Ministry of Food, Agriculture and Consumer Protection in Germany; Ministry of Agriculture in France and Sweden; Ministry of Health, Welfare and Sport in Netherlands; Home Office in United Kingdom; Federal Council in Switzerland; and National Health and Medical Research Council in Australia. The control is responsibility of the Ministry of Science and Technology in Brazil, under two Federal Laws, a Decree and a Resolution; in the State of Parana, there is the State Animal Protection Code. Knowing the work of institutions responsible for the control of the animal experimentation in different countries may help the improvement of this process in Brazil. Such control is urgent due to the need for animal welfare protection and the increasing ethical concern from society in 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.246
GPT teacher head0.463
Teacher spread0.217 · 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.

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
Published2010
Admission routes1
Has abstractyes

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