Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".