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What have we learned about exfoliation syndrome since its discovery by John Lindberg 100 years ago?

2018· review· en· W2790811841 on OpenAlexaff
Samir Nazarali, Faraz Damji, Karim F. Damji

Bibliographic record

VenueBritish Journal of Ophthalmology · 2018
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaUniversity of Ottawa
Fundersnot available
KeywordsMedicineGlaucomaDiseaseEpidemiologyOphthalmologyOptometryDermatologyIntensive care medicinePathology

Abstract

fetched live from OpenAlex

Exfoliation syndrome (XFS) is a systemic disease with significant ocular manifestations, including glaucoma and cataract. The disease impacts close to 70 million people globally and is now recognised as the most common identifiable cause of open-angle glaucoma. Since the discovery of XFS 100 years ago by Dr John G. Lindberg, there has been considerable advancement in understanding its pathogenesis and resulting clinical implications. The purpose of this paper is to summarise information regarding the epidemiology, pathophysiology, ocular manifestations and systemic associations of XFS with the objective of sharing clinical pearls to assist in early detection and enhanced management of patients.

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)0.005
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.003
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 head0.045
GPT teacher head0.348
Teacher spread0.303 · 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

Citations40
Published2018
Admission routes1
Has abstractyes

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