Faculty Opinions recommendation of Reading rehabilitation of individuals with AMD: relative effectiveness of training approaches.
Bibliographic record
Abstract
PURPOSE: To quantify the effects of three vision rehabilitation training approaches on improvements in reading performance.METHODS: Thirty subjects with AMD participated in the training portion of the study. The median age of the subjects was 79 years (range, 54-89 years). The three training modules were: Visual Awareness and Eccentric Viewing (module 1), Control of Reading Eye Movements (module 2), and Reading Practice with Sequential Presentation of Lexical Information (module 3). Subjects were trained for 6 weekly sessions on each module, and the order of training was counterbalanced. All subjects underwent four assessments: at baseline and at three 6-week intervals. Reading performance was measured before and after each training module. A separate group of 6 subjects was randomly assigned to a control condition in which there was no training. These subjects underwent repeated assessments separated by 6 weeks.RESULTS: Reading speeds decreased by an average of 8.4 words per minute (wpm) after training on module 1, increased by 27.3 wpm after module 2, and decreased by 9.8 wpm after module 3. Only the increase in reading speed after module 2 was significantly different from zero. Sentence reading speeds for the control group, who had no reading rehabilitation intervention, was essentially unchanged over the 18 weeks (0.96 ± 1.3 wpm).CONCLUSIONS: A training curriculum that concentrates on eye movement control increased reading speed in subjects with AMD. This finding does not suggest that the other rehabilitation modules have no value; it suggests that they are simply not the most effective for reading rehabilitation. PMID: 21296824
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.142 | 0.035 |
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".