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Record W2312315621 · doi:10.1097/opx.0000000000000700

Expert Views on Innovative Future Uses for Contact Lenses

2015· review· en· W2312315621 on OpenAlexaff
Lyndon Jones, Anuj Chauhan, Nick Di Girolamo, Jim Sheedy, Earl Smith

Bibliographic record

VenueOptometry and Vision Science · 2015
Typereview
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOptometryComputer scienceMedicineData scienceEngineering ethicsEngineering

Abstract

fetched live from OpenAlex

Over the past 10 to 15 years, the availability of new materials and technologies has resulted in revolutionary concepts for contact lenses being proposed that go well beyond correcting vision. These novel uses include their prescribing to deliver topical ocular and systemic drugs, assist with ocular surface disease management, and limit the progression of myopia and novel methods to display visual information. How likely are these concepts to become commercially available, how successful will they be, and what are the potential issues to consider for them to come to market? To answer these questions, a panel of four experts were invited to discuss the benefits and pitfalls of these technologies and what challenges lay ahead of these concepts before their availability. Their responses provide a fascinating insight for the clinician into the likelihood of such revolutionary contact lenses being available in a clinical setting.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
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 head0.106
GPT teacher head0.527
Teacher spread0.421 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations9
Published2015
Admission routes1
Has abstractyes

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