AB106. ORVIS: a directory of tools for vision rehabilitation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The ORVIS infrastructure aims to facilitate the development and availability of valid and adapted tools that will allow functional, perceptual, cognitive and psychological evaluation of low vision clients by researchers and clinicians who work in low vision and visual impairment rehabilitation. Methods: The tools developed or documented within ORVIS Infrastructure are tests or questionnaires which allow, or will allow to assess—in an accurate and reliable manner—characteristics related to visual impairment. The tools in development are: (I) questionnaire de repérage des hallucinations visuelles liées au syndrome de Charles-Bonnet (QR-SCB); (II) repérage des personnes âgées présentant des INDices de déficience VISUELle (IndiVisuel); (III) mesure de l’impact de la déficience visuelle dans les activités quotidiennes (MIDVAQ) and (IV) M’EYE read test. The directory documents 14 tools and offers—within a descriptive sheet—characteristics, components and metrological properties as supported by cited scientific studies. Results: The ORVIS Infrastructure, which aims at the development and availability of assessment tools, fills researchers’ and clinicians’ needs for measurement tools that are valid, effective and appropriate for use with a visually impaired clientele. Such tools are, especially in French, little known and hard to find, and represent a precious resource for those who want to evaluate the efficacy of treatments or interventions. Conclusions: ORVIS is available at www.orvis.vision. Between November 2015 and September 2017, the directory has been accessed 1,383 times by 952 unique visitors.
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.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it