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Record W4281632514 · doi:10.1088/2058-8585/ac73ca

Increased sensitivity of smart contact lenses for continuous intraocular pressure measurement using ring-shaped design

2022· article· en· W4281632514 on OpenAlex
Rick Helgason, Yongjun Lai

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFlexible and Printed Electronics · 2022
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStrain gaugeMaterials scienceLens (geology)Sensitivity (control systems)Piezoresistive effectContact lensRing (chemistry)GlaucomaIntraocular pressureOpticsOptoelectronicsBiomedical engineeringOphthalmologyComposite materialElectronic engineeringEngineeringChemistryMedicinePhysics

Abstract

fetched live from OpenAlex

Abstract Smart contact lenses with continuous intraocular pressure (IOP) sensors are emerging as an alternate system for monitoring the progression and treatment of glaucoma. To date, such sensors have primarily consisted of strain gauges embedded on traditional contact lenses. This work presents a novel smart contact lens design consisting of a ring-shaped contact lens with a piezoresistive strain gauge. We observe an increase in IOP measurement sensitivity of the device with an increase inner diameter of the ring. Ring-shaped sensors with an inner diameter of 2.7 mm show an increase in sensitivity of up to 7.1% and ring-shaped sensors with an inner diameter of 4.7 mm show an increase in sensitivity of up to 17.9%. It is expected that by incorporating a ring-shaped lens, other strain gauge-based smart contact lenses in the literature would experience similar increase in sensitivity.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.225
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.033
GPT teacher head0.265
Teacher spread0.232 · 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