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Record W4399860127 · doi:10.58931/cect.2024.3245

Challenges in the Diagnosis and Management of Anterior Blepharitis

2024· article· en· W4399860127 on OpenAlexaff
Etty Bitton

Bibliographic record

VenueCanadian Eye Care Today · 2024
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBlepharitisMedicineDermatology

Abstract

fetched live from OpenAlex

Blepharitis is defined as inflammation of the eyelids, classified according to anatomical location: anterior (eyelid skin, base of the lashes including the eyelash follicle) or posterior (meibomian glands) blepharitis. Although blepharitis is one of the most common ocular disorders, epidemiological data on the condition is lacking, making prevalence difficult to assess. A 2009 survey of eyecare practitioners reported observing blepharitis in 37%–47% of patients in their clinical practice. This observation may vary depending on the age, sex, and types of patients (i.e., dry eye) in the practice. Younger females are found to have more acute short-term presentation of blepharitis, whereas older, more fair-skinned females present with chronic blepharitis often concurrent with rosacea. Large population‑based studies, using a standardized definition and diagnostic technique, are needed to properly assess the prevalence and incidence of blepharitis and to allow for study comparisons among various age groups. The ocular surface, including the lid margin, has a natural flora or microbiome, which is imperative in maintaining the health and defence mechanism of the ocular surface. This can be affected by age, gender, inflammation, disease, medication, cosmetics, and treatment (systemic or topical). An overgrowth of microbes or an imbalance of the natural flora may result in an inflammatory response, leading to blepharitis, conjunctivitis, keratitis, or a combination of these.

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 score0.820
Threshold uncertainty score0.997

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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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