The use of teleglaucoma at the University of Alberta
Bibliographic record
Abstract
The aim of the teleglaucoma service at the University of Alberta is to improve access for people in northern Alberta who have early-stage glaucoma or who are at risk for glaucoma. Two types of teleglaucoma service are offered: remote and in-house. A standardized approach is used to capture patient information (structured histories, examinations and fundus photographs) which is then sent to a tertiary care centre for grading and recommendations. Only one grader reads and makes management recommendations for each case. Reports are sent electronically. A total of 195 cases have been graded through the remote service since 2008. A total of 62 cases have been graded through the in-house service since 2011. The average reporting time for consultations in the in-house service was 7 days, and it was also 7 days for the remote service. We believe that the use of teleglaucoma can improve the way that patients are diagnosed and managed, both in industrialized and developing countries. Teleglaucoma is currently being used as a screening tool at the Aga Khan University Hospital in Nairobi with mobile units equipped with a fundus camera and a visual field machine.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".