Bibliographic record
Abstract
Keywords: orthoptics, optometry, visual rehabilitation, visual therapy. In the 1920s, Mary Maddox opened a vision rehabilitation center in London, being considered the first orthoptist (an unknown profession in Spain, whose competences fall on Optics‐Optometry). Her father, Ernest E. Maddox, an ophthalmologist, had developed various instruments to investigate binocular vision. The new discipline seeks to improve the binocular state of the patient, affected by symptomatic tropias or phorias, through exercises that train eye movements, ductions, versions, vergences, fixations and saccades. Amblyopia, on the other hand, is still treated by occlusion of the fellow eye, following practices that began in the 18th century (George L. de Buffon). During the 20th century, orthoptic specialists used different instruments, which have survived to this day, for the diagnosis and treatment of deviations. Perhaps the most advanced of them is the synoptophore, capable of determining objective and subjective deviations, the presence of normal or abnormal correspondences, and the presence of suppression scotoma. The synoptophore is also used in rehabilitation, together with the aperture rule, vectograms or the Brock string. However, in the case of tropias and during the 20th century, orthoptic therapy occupies a very marginal place compared to the surgical solution. The Hubel and Wiesel experiments in the 60s and 70s were interpreted restrictively, rooting concepts such as the so‐called critical period, which discouraged any attempt to treat amblyopia beyond occlusion, particularly in adulthood. However, research carried out from the second half of the 20th century to nowadays provides evidence of the usefulness of vision rehabilitation in the treatment of strabismus and non‐strabismus visual dysfunctions, and in the recovery of amblyopia in adulthood. Basic research led by Dennis M. Levi of the University of California at Berkeley and Robert F. Hess of McGill University, as well as clinical research by the Paediatric Eye Disease Investigator Group, PEDIG, are good examples. New technologies based on computers are currently renewing and revitalizing orthoptic practice, both in diagnosis and treatment. Eye‐trackers combined or not with Virtual Reality allow (a) to record eye movements accurately and objectively, and to identify visual behaviour and deficits, and (b) to train those movements, providing positive feedback to the patient. Screens have evolved from conventional models, later 3D and finally Virtual Reality, allowing dynamic exercises and avoiding other limitations, such as postural ones. Software algorithms adapt the difficulty of the exercises to patient's performance, record therapy compliance, and store the results in the cloud for remote control of home therapy. In addition, gamification techniques allow increasing the patient's motivation and adherence to treatment. These improvements are essential in perceptual learning, the paradigm of the new visual rehabilitation model.
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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 | 0.000 | 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 | 0.000 | 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 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".