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Record W2183878638 · doi:10.20506/rst.30.1.2031

Risk analysis and its link with standards of the World Organisation for Animal Health

2011· review· en· W2183878638 on OpenAlexaff
Katsuaki Sugiura, Noel Murray

Bibliographic record

VenueRevue Scientifique et Technique de l OIE · 2011
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsAnimal healthTreatyBusinessRisk assessmentPhytosanitary certificationRisk analysis (engineering)World tradeRisk managementEnvironmental healthInternational tradeVeterinary medicinePolitical scienceMedicineComputer scienceEconomic growthComputer securityLawEconomics

Abstract

fetched live from OpenAlex

Among the agreements included in the treaty that created the World Trade Organization (WTO) in January 1995 is the Agreement on the Application of Sanitary and Phytosanitary Measures (SPS Agreement) that sets out the basic rules for food safety and animal and plant health standards. The SPS Agreement designates the World Organisation for Animal Health (OIE) as the organisation responsible for developing international standards for animal health and zoonoses. The SPS Agreement requires that the sanitary measures that WTO members apply should be based on science and encourages them to either apply measures based on the OIE standards or, if they choose to adopt a higher level of protection than that provided by these standards, apply measures based on a science-based risk assessment. The OIE also provides a procedural framework for risk analysis for its Member Countries to use. Despite the inevitable challenges that arise in carrying out a risk analysis of the international trade in animals and animal products, the OIE risk analysis framework provides a structured approach that facilitates the identification, assessment, management and communication of these risks.

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)0.014
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.006
Science and technology studies0.0010.006
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.070
GPT teacher head0.334
Teacher spread0.265 · 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 designNot applicable
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

Citations12
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueRevue Scientifique et Technique de l OIESame topicAnimal Disease Management and EpidemiologyFrench-language works237,207