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Record W2009482119 · doi:10.1167/iovs.08-1843

The Interblink Interval I: The Relationship between Sensation Intensity and Tear Film Disruption

2009· article· en· W2009482119 on OpenAlexaff
Jalaiah Varikooty, Trefford Simpson

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2009
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSensationIntensity (physics)AudiologyOphthalmologyMedicinePsychologyOpticsNeurosciencePhysics

Abstract

fetched live from OpenAlex

PURPOSE: To find the relationship between tear film drying and sensation during the interblink period. METHODS: One eye was taped shut, and after a blink the subjects were required to keep the other eye open. Digital video images of the ocular surface (with fluorescein) were obtained using a slit lamp biomicroscope while 23 subjects rated the intensity of the ocular surface sensation by adjusting a one-turn potentiometer to represent the strength of the sensation. They were trained to use the potentiometer before the data were collected. In addition, the characteristics of the sensation as spoken by the subject were recorded. RESULTS: The sensation was generally triphasic, with initial constant sensation and a subsequent biphasic period, with intensity increasing slowly followed by a rapid increase before the subjects blinked (correlations were all r > 0.95). Tear film drying dynamics were also biphasic, and drying and sensation were strongly associated, with a correlation of 0.94 between the break in the bilinear functions of sensation and drying. CONCLUSIONS: The method provides novel information about the development of ocular sensation during ocular surface drying. As evidenced by the complex functions required to adequately describe the relationships, tear film drying and ocular surface sensations are associated in complex ways.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
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 head0.072
GPT teacher head0.366
Teacher spread0.295 · 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.

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

Citations28
Published2009
Admission routes1
Has abstractyes

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