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Record W4391024715 · doi:10.15353/cjo.v49i2.4546

An Overview on the Use of a Low Magnification Telescope in Low Vision

2021· article· en· W4391024715 on OpenAlexvenueno aff
George C. Woo

Bibliographic record

VenueCanadian journal of optometry/CJO. Canadian journal of optometry · 2021
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsEyepieceTelescopeField of viewMagnificationOpticsLens (geology)Refracting telescopePhysicsOptical telescopeComputer scienceExit pupilReflecting telescopeEntrance pupilAperture (computer memory)Computer visionArtificial intelligencePupilAcoustics

Abstract

fetched live from OpenAlex

A Galilean telescope in its simplest form is a two element system consisting of a positive lens as an objective and a nega­tive lens as an eyepiece. The system is restricted to lower magnifications and smaller fields of view in comparison with a Keplerian telescope. The image through the system, however, is always erect permitting its use for distance viewing for partially sighted patients. Other optical factors besides magnifica­tion and field of view that need to be con­sidered include exit pupil size, focus adjustability, vertex distance, and image quality in terms of color and brightness. Such non optical factors as weight, port­ability, ease of use, appearance and cost are also influencing variables'. In this overview on the clinical use of low power telescopes in the examination room, only a few properties will be exa­mined. The use of a low power full-field telescope in subjective and objective refractions will be discussed. Magnifica­tion through a telescope will also be elaborated upon.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.151
GPT teacher head0.492
Teacher spread0.342 · 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.

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
Published2021
Admission routes1
Has abstractyes

Explore more

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