Eye movements when viewing natural scenes with normal vision and simulated scotomas
Bibliographic record
Abstract
Purpose: Age-related macular degeneration (AMD) results in central retinal defects due to photoreceptor degeneration (dry AMD) or photoreceptor distortion by abnormal blood vessel growth (wet AMD). Individuals with AMD must compensate by making use of the unaffected peripheral vision. Consequently, this might lead to alternative eye movement (EM) strategies when performing visual search tasks, resulting in an increase in EM frequency. Methods: We recorded binocular EM (Eyelink 1000 tracker) while observers performed two natural tasks: visual search and free-viewing. Using the recorded eye position, images at the current fixation were either distorted (wet AMD), removed (dry AMD) or left intact (control, no AMD). Results: Under the simulated AMD conditions, fixation frequency and duration increased, and saccades were of greater amplitude. Behavioural results show that it took longer to find the target with simulated AMD conditions in comparison to the control condition. Type of AMD also has an effect on the EMs, with fixation duration being longer, and saccade amplitudes being smaller for wet AMD in comparison to dry AMD. In the free-viewing experiment, similar results were obtained. Conclusions: These results imply that while visual tasks can still be performed with central vision loss, they lead to impaired visual performance. In addition, different EM strategies between wet and dry AMD lead us to the conclusion that visual aids and training programs designed to incorporate remaining peripheral vision must take into consideration the cause of the scotoma.
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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 | 0.000 | 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".