Deficits and Adaptation of Eye-Hand Coordination During Visually Guided Reaching Movements in People with Amblyopia
Bibliographic record
Abstract
Introduction Amblyopia is a visual impairment of one eye caused by inadequate use during early childhood and cannot be corrected by optical means (American Academy of Ophthalmology, 2007). Clinically, it is usually defined as a visual acuity of 20/30 or worse without any apparent structural abnormality in the affected eye. Amblyopia is a significant public health issue because it is the number one cause of monocular visual loss worldwide, affecting 3 to 5 percent of the population in the Western world (Attebo et al., 1998; Hillis, 1986). Because of its prevalence, the financial burden of amblyopia is enormous. A major U.S. study estimated that untreated amblyopia causes a yearly loss of US$7.4 billion in earning power and a corresponding decrease in the gross domestic product. An estimated US$341 million is spent each year to prevent and treat amblyopia (Membreno et al., 2002). Unfortunately, approximately 50 percent of patients do not respond to therapies (Holmes, Beck, et al., 2003; Holmes, Kraker, et al., 2003; The Pediatric Eye Disease Investigator Group [PEDIG], 2003; Repka et al., 2004, 2008; Scheiman et al., 2005). The personal cost of amblyopia is also substantial. People with amblyopia (including those treated successfully and those whose treatment failed) often have limited career choices and reduced quality of life such as reduced social contact, distance and depth estimation deficits, visual disorientation, and fear of losing vision in the better eye (van de Graaf et al., 2004).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".