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Record W2944762169 · doi:10.15353/cjo.77.486

Vernal Keratoconjunctivitis and its Management Challenges

2015· article· en· W2944762169 on OpenAlexvenueno aff
Onyeahiri Collins

Bibliographic record

VenueCanadian journal of optometry/CJO. Canadian journal of optometry · 2015
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsnot available
Fundersnot available
KeywordsVernal keratoconjunctivitisMedicineKeratoconjunctivitisDiseaseAllergic conjunctivitisDermatologyPalpebral fissurePediatricsIncidence (geometry)AsthmaSurgeryImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Vernal keratoconjunctivitis (VKC) is an allergic, bilateral, recurrent inflammatory disorder of the conjunctiva and the cornea that has a seasonal incidence. It affects young males more than females in age bracket of 3 to 16. In the majority of cases, symptoms resolve at puberty, but some may run into adulthood. Diagnosis is based typically on clinical signs and symptoms. The cause of the disease is not clearly known, but it is often associated with atopic diseases such as asthma or eczema and is probably due to a longstanding allergic reaction. The disease consists clinically of the palpebral, limbal and mixed types. Its management has been a great challenge to eye care providers because of its recurrent nature, the large number of individuals who are affected, wrong diagnoses, and lack of judicious drug administration. The disease has the potential of producing serious vision-threatening complications if not adequately managed. This case report also reviews the diagnosis and management options for patients with mixed VKC and demonstrates the importance of the clinician’s role in taking a careful case history and in modifying treatment when necessary throughout care.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0030.007
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 head0.028
GPT teacher head0.299
Teacher spread0.271 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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Same venueCanadian journal of optometry/CJO. Canadian journal of optometrySame topicOcular Surface and Contact LensFrench-language works237,207