The amblyopic acuity deficit: impact on the identification of letters distorted by spatial scrambling algorithms
Bibliographic record
Abstract
Abstract The letter acuity impairment in the amblyopic eye often exceeds predictions made from the cut-off spatial frequency for grating detection. Spatial scrambling in the amblyopic eye’s projections to the visual cortex has been proposed to bear some responsibility for this additional deficit. Using a novel stimulus algorithm that creates spatially scrambled bandpass letters, we generated stimuli simulating either: i) “cortical scrambling” at the output of oriented model “simple cells”, or ii) “subcortical scrambling” of isotropic subunits that combine to form these simple cells. We also investigated a more conventional “noise masking” with bandpass noise. We performed two bandpass letter identification experiments, equating the stimuli shown to each eye by normalising either: i) their contrast, presenting them at four times their contrast detection threshold; or ii) their spatial scale, presenting them at twice the participant’s acuity threshold for each eye. At the group level, we found that the amblyopic eye is less efficient at performing letter identification in bandpass noise. We did not find an overall significant difference with either scrambling type when comparing efficiency between the amblyopic and fellow eye, but we did find such a difference when partitioning our participants by their stereopsis ability. In further analyses of the pattern of mistakes, we found the amblyopic eye shows a distinctive behaviour which correlates with the acuity deficit for both types of scrambling. These results demonstrate that our scrambled stimuli interrogate a component of amblyopic vision that is functionally distinct from that addressed by contrast noise masking.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".