The multi-disciplinary nature of low vision rehabilitation~-- A case report
Bibliographic record
Abstract
This paper presents the case of a 47-year-old female with low vision secondary to high myopic macular degeneration who remains active in the work force as a spiritual and religious care coordinator for a large institution. An ophthalmologist with a specialty in low vision rehabilitation initially assessed the client. The ophthalmologist prescribed optical devices which used residual retinal vision available at preferred retinal loci. This availed better vision for viewing targets located at far, near and intermediate distances from the client. An optician provided and dispensed the devices prescribed to the client. Additionally, the ophthalmologist made a referral to an occupational therapist. The occupational therapist conducted a series of sessions to further enhance reading and writing skills and a work place assessment aimed at optimizing workplace conditions in order to achieve optimal functional vision. This case illustrates and emphasizes the multi-disciplinary nature of low vision rehabilitation, which involved in this case co-operation between ophthalmology, occupational therapy and opticianry.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".