Contrast sensitivity channels in amblyopia: a meta-factor-analysis
Bibliographic record
Abstract
Amblyopia is characterized by a reduced visual acuity and lower contrast sensitivity in the amblyopic eye, particularly at high spatial frequencies. Despite this generalization, there are also large inter-individual differences of contrast sensitivity between amblyopic observers. In this study, we analyzed these differences to investigate the spatial frequency channels in amblyopia. To determine the spatial frequency channels in amblyopia, we ran a meta factor-analysis on 5 datasets taken from our previous studies using a principal component analysis followed by a varimax rotation of the components. In the range of 0.25 to 10 c/d, this analysis revealed two spatial frequency channels: one low- and one high-, peaking around 0.5 and 2 c/d respectively. Interestingly, those presented very similar tuning in the amblyopic eye and the fellow eye. The only major difference was in the weight attributed to the high frequency channel. It was reduced by approximately 50% in the amblyopic eye. Nevertheless, the sensitivities in these 2 channels were correlated for both the amblyopic eye and fellow eye. These findings suggest that there is no fundamental mechanistic deficit in contrast sensitivity of amblyopia and that high spatial frequencies might just be attenuated in the amblyopic eye. Our findings support the usage of binocular therapies that rely on the premise of rebalancing the relative contrasts between both eyes and the assumption that both eyes can be binocularly fused.
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.030 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".