Enhanced access to glaucoma diagnosis and management via patient centered collaborative teleglaucoma (TG) approaches in Northern Alberta and in Ethiopia
Bibliographic record
Abstract
Abstract We describe patient centered collaborative TG care models in Northern Alberta & Ethiopia (1‐3). Optometrists or technicians select high risk patients & those with possible early glaucoma, & upload structured history, exam, & diagnostic tests. Data is stored on a secure web platform (teleophthalmology.com) & graded by glaucoma specialists with recommendations for care. Validation included comparison of optic nerve features with digital 3D & 2D vs 3D slide film, and in person vs virtual exam. Stakeholder feedback improved front line & grading protocols. Some TG consults are ineffective due to patient cooperation, media opacities, & technology challenges (4). Opportunities exist for mobile phone photography of the anterior & posterior segment & leveraging ‘m health’ for e‐learning, research & patient education. Future research could focus on validation of TG models & optimal use of finite resources, including cost & comparative effectiveness. 1. J Telemed Telecare 2012;18(7):367‐73 2. MEAJO;2013:20(2):142‐9 3. Clin Exp Optom. 2013 Jun 13 4. MEAJO 2013;20(2):150‐7 Acknowledgements: Drs A Giorgis, A Mulugeta, F Kassam, S Arora, A Kurji, M Edwards, A Moalin & Secure Diagnostic Imaging
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".