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Record W3154036418

Overview of animal welfare standards and initiatives in selected EU and third countries

2010· article· en· W3154036418 on OpenAlexaboutno aff
Otto Schmid, Rahel Kilchsperger

Bibliographic record

VenueOrganic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture) · 2010
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
FundersFilhaChina Agricultural UniversityGoverno BrasilDepartment of Agriculture, Fisheries and Forestry, Australian GovernmentEuropean CommissionAustralian Government
KeywordsLegislationContext (archaeology)European unionWelfareAnimal welfareAction planPolitical scienceEconomic growthChinaBusinessGeographyInternational tradeEconomicsLawEcology
DOInot available

Abstract

fetched live from OpenAlex

The analysis and comparison of animal welfare standards and initiatives in eight European and selected 3rd countries was compiled as part of the EU funded project “Good animal welfare in a socio-economic context: Project to promote insight on the impact for the animal, the production chain and European society of upgrading animal welfare standards (EconWelfare)”. The project provides scientific support for the development of European policies implementing the Community Action Plan on the Protection and Welfare of Animals for 2006-2010. \nTaking into account the cultural and geographic differences within the EU and the importance of livestock production in individual member states, the synthesis focused on relevant standards and initiatives in Germany, Spain, Italy, the Netherlands, Poland, Sweden, the United Kingdom and Macedonia. A comparative analysis of welfare standards was made of the legislation from the EU itself, selected EU countries as well as from Australia, Brazil, Canada, Switzerland, China, New Zealand and the United States of America.

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)0.010
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0170.031
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.111
GPT teacher head0.414
Teacher spread0.303 · 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
GenreReview

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

Citations26
Published2010
Admission routes1
Has abstractyes

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Same venueOrganic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture)Same topicAnimal Behavior and Welfare StudiesFrench-language works237,207