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Record W2004186717 · doi:10.1097/opx.0b013e31804bdc27

Contact Lenses in Suboptimal Environments

2007· article· en· W2004186717 on OpenAlexaboutno aff
Loretta Szczotka‐Flynn, Lyndon Jones, Donald R. Korb, Debbie F Sweeney

Bibliographic record

VenueOptometry and Vision Science · 2007
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsnot available
Fundersnot available
KeywordsContact lensOptometryLens (geology)OpticsComputer scienceMedicinePhysics

Abstract

fetched live from OpenAlex

For contact lenses to truly succeed so that they become the first choice for the correction of refractive error—even over spectacles—a number of lingering issues remain. In a perfectly controlled sterile setting, contact lenses can be adequately comfortable and successful. However, in the real world complete with dust and pollution, and amid populations of patients that vary in ocular surface structure and function; succeeding with contact lenses for the masses has proven to be challenging. What Constitutes a Suboptimal Environment? One could argue everyday living conditions are nonideal for the majority of contact lens wearers on this planet. The smoke at the corner bar, reading never-ending e-mails, or even traveling to work in an air-conditioned or heated car can compromise contact lens wear. Think about it: contact lenses are asked to peacefully coexist within the protein and lipid-rich tear film of a patient that lives in a world filled with ubiquitous organisms just waiting to become opportunistic pathogens. Additionally, contact lenses not only increase the evaporation rate of the tear film but can create their own suboptimal environment by adding hypoxic stress with daily and especially overnight use, or through the solutions in which they are bathed. Fortunately, contact lens associated infection remains rare, and comfort is continually improving. Certainly, industry has given us tools to efficaciously treat just about any refractive error while attempting to combat hypoxia and discomfort. Obviously, they are going in the right direction if already 140 million people wear contact lenses globally. Yet, what do we need to do to retain these wearers and increase the acceptance of contact lenses in the other 450 million people that need and can afford them? The pages that follow outline tremendous research happening globally. It includes fundamental mechanisms of how contact lenses positively and negatively alter the optical and physiological properties of the eye. The original papers and reviews found herein encompass the quality work happening in our profession and the contact lens research community. As Professor Holden states: “the visual advantages of contact lenses will only be realized if lenses disturb the homeostasis of the eye and its defense systems as little as possible, or if possible enhance them.” Loretta Szczotka-Flynn Cleveland, OH Lyndon Jones Waterloo, Canada Donald Korb Boston, MA Debbie Sweeney Sydney, AustraliaFigure: From left to right: Loretta Szczotka-Flynn, OD, MS, FAAO; Lyndon W. J. Jones, FCOptom, PhD, FAAO; Donald R. Korb, OD, FAAO; Deborah F. Sweeney, Boptom, PhD, FAAO.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.396
Teacher spread0.383 · 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 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

Citations0
Published2007
Admission routes1
Has abstractyes

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