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Record W2313618556 · doi:10.1097/opx.0b013e3182691454

Measuring the Modulus of Silicone Hydrogel Contact Lenses

2012· article· en· W2313618556 on OpenAlexaff
Caleb Horst, Benjamin Brodland, Lyndon Jones, G. Wayne Brodland

Bibliographic record

VenueOptometry and Vision Science · 2012
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsEnvironmental Studies Association of CanadaUniversity of Waterloo
FundersCooperVision
KeywordsLens (geology)Materials scienceModulusElastic modulusContact lensComposite materialOpticsDioptreTangent modulusOptical powerStrain gaugePhysics

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to demonstrate a novel method for measuring the modulus of contact lenses in their as-received, variable-thickness form and to determine whether modulus varies with location within commercial lenses and whether it is dependent on lens geometry and temperature. METHODS: The thickness profiles of lenses having powers from -8 diopters (D) to +4 D were measured using a Rehder electronic thickness gauge. Strip-shaped specimens having a width of 5.5 mm were then cut from the lenses. Graphite particles were sprinkled on the specimen surface so that its motions could be tracked using digital image-correlation techniques. The specimens were mounted in a BioTester test system using BioRakes (rather than clamps) and stretched uniaxially until all parts of the lens between the attachment points had elongated by at least 10%. This procedure allowed local modulus values to be determined at 110 locations over the surface of each lens and any property variations within the lenses to be characterized. Tests were performed at 5, 23, and 37°C. RESULTS: Material modulus was found to be essentially constant within any given lens and was independent of the optical power of the lens. Young's Modulus values ranged from 0.3 to 1.9 MPa, depending on the lens manufacturer and product, and some lens materials showed a decrease in modulus with temperature. For the materials tested, those with lower water content had a tendency to exhibit higher moduli. CONCLUSIONS: Testing of the kind reported here is important for assessing the efficacy of current and proposed contact lens materials and designs, especially if such designs make use of variable properties to enhance function or fit.

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: Bench or experimental · Consensus signal: Bench or experimental
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 communication0.0000.001
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 head0.028
GPT teacher head0.377
Teacher spread0.349 · 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 designBench or experimental
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

Citations52
Published2012
Admission routes1
Has abstractyes

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