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Record W3017691845 · doi:10.1002/mds3.10086

A novel non‐invasive wearable sensor for intraocular pressure measurement

2020· article· en· W3017691845 on OpenAlexafffund
Angelica Campigotto, Yongjun Lai

Bibliographic record

VenueMedical Devices & Sensors · 2020
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsQueen's University
FundersQueen's University
KeywordsIntraocular pressureGlaucomaMedicinePressure sensorOphthalmologyOptic nerveWearable computerComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Glaucoma is a chronic eye disease where an increase in intraocular pressure (IOP) permanently damaging the optic nerve leading to irreversible vision loss. Intraocular pressure is the main factor for monitoring the progression of glaucoma and has been found to fluctuate throughout the day. A continuous monitoring system can track the fluctuations in the intraocular pressure throughout the day, improving the management of the disease. A novel non‐invasive wearable sensor was created to monitor the fluctuating corneal curvature of the eye and directly relate the deformation to the intraocular pressure. The wearable sensor was able to capture on average 40.8 µm/mmHg with a standard deviation of 29.4 in fluid location per increase in intraocular pressure with an ability to return over 80% back to its original position indicating a good ability to accurately track the fluctuations in the IOP.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.259
Teacher spread0.233 · 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

Citations20
Published2020
Admission routes2
Has abstractyes

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