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Record W1992714541 · doi:10.1504/ijram.2010.035935

Managing the risks of bovine spongiform encephalopathy: a Canadian perspective

2010· article· en· W1992714541 on OpenAlexaffabout
William Leiss, Michael G. Tyshenko, Daniel Krewski, Neil R. Cashman, Louise Lemyre, Mustafa Al Zoughool, Carol Amaratunga

Bibliographic record

VenueInternational Journal of Risk Assessment and Management · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of British ColumbiaUniversity of OttawaInstitute of Population and Public Health
Fundersnot available
KeywordsBovine spongiform encephalopathyRisk managementPerspective (graphical)Risk analysis (engineering)Set (abstract data type)Management sciencePolitical scienceBusinessEngineering ethicsComputer scienceEngineeringDiseaseMedicinePrion proteinArtificial intelligencePathology

Abstract

fetched live from OpenAlex

This paper reviews the history of the risk management challenges faced by many countries and regions of the world which have had cases of bovine spongiform encephalopathy (BSE) from 1986 to the present. The paper first summarises the nature of prion diseases from a scientific perspective, and then presents an overview of the findings of an extensive set of country case studies, devoting special attention to the Canadian case. It derives from these studies the need to reconstruct the frameworks which have been guiding risk management decision making, using forma schemata based on a step-by-step approach. The paper presents and illustrates a revised format for an integrated risk management framework, including a set of specific and explicit objectives that should guide the use of this framework in practice, and concludes by raising policy issues that are currently outstanding with respect to the management of prion disease 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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.628
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.327
Teacher spread0.316 · 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

Citations8
Published2010
Admission routes2
Has abstractyes

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