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Apparent time‐dependent differences in inferior tear meniscus height in human subjects with mild dry eye symptoms

2007· article· en· W2087036827 on OpenAlexaff
Sruthi Srinivasan, Colin Chan, Lyndon Jones

Bibliographic record

VenueClinical and Experimental Optometry · 2007
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMedicineAsymptomaticOphthalmologyDry eyesSchirmer testDrynessTearsContact lensArtificial tearsSurgery

Abstract

fetched live from OpenAlex

PURPOSE: The aim of the study was to track the volume of tears contained in the inferior tear meniscus over the course of the day in subjects with symptoms of mild dry eye and a control asymptomatic group. METHODS: Forty non-contact lens-wearing subjects (aged 27 +/- 6 years) were enrolled in this investigator-masked study. They were divided into 'dry eye' (DE) and 'non-dry eye' (NDE) individuals based on their responses to the Allergan Subjective Evaluation of Symptoms of Dryness (SESOD) questionnaire. Measurement of the tear meniscus height (TMH) was undertaken on the centre of the right eye at 9:00 am, noon, 3:00 pm, 6:00 pm and 9:00 pm on the lower lid using a non-contact, non-invasive optical coherence tomographer (OCT). The TMH was determined from scanned images using customised software. RESULTS: A monotonous and significant reduction in the central TMH occurred over the course of the day in both groups (p < 0.05), with the values constantly decreasing (NDE = 0.162 to 0.125 mm; DE = 0.154 to 0.121 mm). While the TMH values in the DE group were always lower than the NDE group, these were not significantly different at any time (p > 0.05). CONCLUSIONS: A diurnal reduction in tear volume, as assessed by evaluation of the inferior TMH, may be one of the reasons responsible for the common increase in end-of-day ocular dryness symptoms reported by many patients in clinical practice.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.021
GPT teacher head0.364
Teacher spread0.342 · 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 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

Citations54
Published2007
Admission routes1
Has abstractyes

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