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Record W7006844164

Xenotropic Murine Leukemia Virus-Related Virus as a Case Study: Using a Precautionary Risk Management Approach for Emerging Blood-Borne Pathogens in Canada

2012· other· en· W7006844164 on OpenAlexaboutno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2012
Typeother
Languageen
FieldEnvironmental Science
TopicEducational Reforms and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsGammaretrovirusChronic fatigue syndromeDiseasePopulationEpidemiologyLeukemiaVirus
DOInot available

Abstract

fetched live from OpenAlex

In October 2009 it was reported that 68 of 101 patients with chronic fatigue syndrome (CFS) in the United States, when tested, were infected with a novel gamma retrovirus, xenotropic \n \nmurine leukemia virus-related virus (XMRV) (Lombardi et al., 2009). XMRV is a recently \n \ndiscovered human gammaretrovirus first described in prostate cancers that shares \n \nsignificant homology with murine leukemia virus (MLV) (Ursiman et al., 2006). It is known \n \nthat XMRV can cause leukemias and sarcomas in several rodent, feline, and primate species \n \nbut has not been shown to cause disease in humans. XMRV was detectable in the peripheral \n \nblood mononuclear cells (PBMCs) and plasma of individuals diagnosed with CFS \n \n(Lombardi et al., 2009). After this report was published there was a great deal of uncertainty \n \nsurrounding this emergent virus and its involvement in the etiology of CFS. The uncertainty \n \nwas, in part, due to CFS being a complex, poorly understood multi-system disorder with \n \ndifferent disease criteria used for its diagnosis. CFS, also known as Myalgic \n \nEncephalomyelitis (ME), is a debilitating disease of unknown origin that is estimated to \n \naffect 17 million people worldwide. The initial report connecting XMRV to prostate cancers \n \nand CFS garnered significant media and scientific interest since it provided a potential \n \n \n \nSusie ElSaadany2**, Tamer Oraby1 \n \n* \n \nDaniel Krewski1, 4 and Peter R. Ganz5 \n \n1McLaughlin Centre for Population Health Risk Assessment, Institute of Population Health, University of \n \nOttawa, Ontario, Canada \n \n2Blood Safety Surveillance and Health Care Acquired Infections Division, Centre for Communicable Diseases and \n \nInfection Control, Public Health Agency of Canada, Ottawa, Ontario, Canada \n \n3Aspinall and Associates, Cleveland House, High Street, and Earth Sciences, Bristol University, Bristol, United \n \nKingdom \n \n4Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, Ottawa, \n \nOntario, Canada \n \n5Health Canada, Director’s Office, Ottawa, Ontario, Canada \n \n** Corresponding Author \n \n, Marian Laderoute2 \n \n, Jun Wu2 \n \n, Willy Aspinall3 \n \n, \n \nwww.intechopen.com \n \n32 The Continuum of Health Risk Assessments \n \nexplanation for the disease but also an avenue for possible therapeutic treatments since \n \nXMRV is known to be susceptible to some anti-retroviral drugs (Cohen, 2011).

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.345
Threshold uncertainty score0.694

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0090.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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