Bibliographic record
Abstract
T presentation focusses on the disparity between the demonstrated effectiveness of low vision rehabilitation and the significant barriers which still exist to referral for, and access to, low vision rehabilitation services. Some of these barriers are societal and due to lack of information. But some are due to referral patterns of eye care professionals. This talk covers the research which has demonstrated the effectiveness of low vision rehabilitation and the factors which influence access to low vision services as well as those that influence eye care professional’s referral patterns. A new model is proposed which changes the way that low vision is conceived and which eye care professionals would be involved in low vision. Low vision care extends from the recognition of a potential low vision case to assessment of impairment, recognition of likely disabilities, goal setting, triage through to basic low vision rehabilitation and finally to managing patients with complex goals and multiple challenges. The levels of visual impairment at which low vision services are likely to be required is discussed. When considered in this light, it is suggested that all eye care professionals should be involved in low vision care, but that the level at which they are involved can be selected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".