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Record W2076816996 · doi:10.1167/iovs.06-0731

Suprathreshold Contrast Matching in Maculopathy

2007· article· en· W2076816996 on OpenAlexaff
Ming Mei, Susan J. Leat

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2007
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaculopathyContrast (vision)Macular degenerationOphthalmologyMedicineAudiologyAge-related maculopathyRetinopathyOpticsDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

PURPOSE: To compare suprathreshold contrast perception among three groups of participants with maculopathy (atrophic age-related macular degeneration [ARMD], exudative ARMD, and juvenile macular dystrophy [JMD]) and to compare suprathreshold contrast matching between controls and subjects with maculopathy. METHODS: Three groups of subjects with macular disorders (13 atrophic ARMD, 14 exudative ARMD, and 8 JMD) and one group of control subjects (15 subjects 50 years and older) participated. Contrast sensitivity (CS) up to 8.53 cycles per degree (cpd) was measured with a temporal two-alternative forced-choice staircase procedure. Suprathreshold contrast matching was measured using a method of limits. A 0.58 cpd sine-wave grating was the standard; the subject was asked to match the contrast of gratings of different spatial frequencies. RESULTS: Subjects with maculopathy showed marked deficits of contrast threshold. Suprathreshold contrast constancy was shown, though deficits were observed in absolute matches compared with control subjects. The slopes of matched contrast against standard contrast for the subjects with maculopathy were significantly different from those for the controls, and these differences were in the direction that implies compensation for differences in thresholds. There were no significant differences among the three groups of subjects with maculopathy. CONCLUSIONS: In this study, the authors observed a degree of contrast constancy in subjects with maculopathy, though there were still deficits compared with control subjects. This is discussed in terms of gain of the visual system adjusting to compensate for CS losses (though incompletely) or contrast overconstancy, present in normal peripheral vision, which helps to compensate for CS loss.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.389
Teacher spread0.340 · 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

Citations25
Published2007
Admission routes1
Has abstractyes

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