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Record W2063277162 · doi:10.1155/2010/709791

Animal Models of CNS Viral Disease: Examples from Borna Disease Virus Models

2010· article· en· W2063277162 on OpenAlex
Marylou V. Solbrig

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInterdisciplinary Perspectives on Infectious Diseases · 2010
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of HealthUniversity of Manitoba
KeywordsDiseaseVirologyMeningoencephalitisVirusAsymptomaticMedicineNeurochemicalBiologyNeurosciencePathology

Abstract

fetched live from OpenAlex

Borna disease (BD), caused by the neurotropic RNA virus, Borna Disease virus, is an affliction ranging from asymptomatic to fatal meningoencephalitis across naturally and experimentally infected warmblooded (mammalian and bird) species. More than 100 years after the first clinical descriptions of Borna disease in horses and studies beginning in the 1980's linking Borna disease virus to human neuropsychiatric diseases, experimentally infected rodents have been used as models for examining behavioral, neuropharmacological, and neurochemical responses to viral challenge at different stages of life. These studies have contributed to understanding the role of CNS viral injury in vulnerability to behavioral, developmental, epileptic, and neurodegenerative diseases and aided evaluation of the proposed and still controversial links to human disease.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.018
GPT teacher head0.305
Teacher spread0.287 · 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