On the Maintenance of Normal Ocular Dominance and a Possible Mechanism Underlying Refractive Adaptation
Bibliographic record
Abstract
PURPOSE: Do humans with uncorrected anisometropia who have not developed anisometropic amblyopia exhibit a shift in ocular dominance nonetheless, reflecting a more subtle form of deprivation? Also, is such a change in dominance, if it occurs, permanent or could it be rectified by an extended period of optical correction? METHODS: A total of 25 normal controls (27.5 ± 2.1 years; mean ± SD); 28 anisometropes (20.7 ± 5.6 years) who were fully corrected for more than 16 weeks prior to this investigation; and 24 anisometropes who had never been corrected (21.2 ± 9.8 years) participated in this study. Sensory eye dominance of observers was measured using the binocular phase combination paradigm to find an interocular contrast ratio at which the contributions of each eye to the binocularly fused percept were equal (i.e., the balance point measure of ocular dominance). RESULTS: Controls exhibited a balance point close to unity (0.91 ± 0.05), while the two groups of anisometropes exhibited a clear binocular imbalance (uncorrected anisometropes, 0.51 ± 0.28; corrected anisometropes, 0.70 ± 0.19); both were significantly different from controls (P < 0.001). The imbalance was less severe in corrected anisometropes compared with uncorrected anisometropes (P = 0.004). CONCLUSIONS: We find that anisometropia is associated with an ocular imbalance even in the absence of amblyopia. This abnormality is weaker in anisometropes who have worn an optical correction for some time, suggestive that a better optical status leads to a better binocular status.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".