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Record W4281999737 · doi:10.1111/vop.13002

A review of investigated risk factors for developing equine recurrent uveitis

2022· review· en· W4281999737 on OpenAlex
Nicole B. Kingsley, Lynne S Sandmeyer, Rebecca R. Bellone

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.

Bibliographic record

VenueVeterinary Ophthalmology · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicT-cell and Retrovirus Studies
Canadian institutionsUniversity of Saskatchewan
FundersMorris Animal Foundation
KeywordsDiseaseEtiologyMedicineUveitisBlindnessIntensive care medicineImmunologyBioinformaticsPathologyBiology

Abstract

fetched live from OpenAlex

Equine recurrent uveitis (ERU) is an ocular inflammatory disease that can be difficult to manage clinically. As such, it is the leading cause of bilateral blindness for horses. ERU is suspected to have a complex autoimmune etiology with both environmental and genetic risk factors contributing to onset and disease progression in some or all cases. Work in recent years has aimed at unraveling the primary triggers, such as infectious agents and inherited breed-specific risk factors, for disease onset, persistence, and progression. This review has aimed at encompassing those factors that have been associated, implicated, or substantiated as contributors to ERU, as well as identifying areas for which additional knowledge is needed to better understand risk for disease onset and progression. A greater understanding of the risk factors for ERU will enable earlier detection and better prognosis through prevention and new therapeutics.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.193
GPT teacher head0.378
Teacher spread0.185 · 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