Impact of 11 years of glaucoma research funding: Glaucoma Research Society of Canada (2010–2020)
Bibliographic record
Abstract
OBJECTIVE: The Glaucoma Research Society of Canada (GRSC) is Canada's only nonprofit organization dedicated to funding peer-reviewed glaucoma research. This study evaluates the impact of GRSC-funded projects using established research productivity metrics. DESIGN: Retrospective study. METHODS: GRSC-funded grants from 2010 to 2020 were analyzed, including project details and funding amounts. Research productivity was assessed by (1) the number of peer-reviewed publications and (2) the number of conference presentations at major North American meetings. Publications were identified via PubMed searches of grant recipients, ensuring alignment with GRSC-funded topics. Conference presentations were determined by reviewing accepted abstracts from 5 key ophthalmology meetings: the Canadian Ophthalmological Society, American Society of Cataract and Refractive Surgery, American Academy of Ophthalmology, American Glaucoma Society, and Association for Research in Vision and Ophthalmology. Research output was analyzed in relation to funding costs. RESULTS: Of 135 grants totaling $2,220,822, 84 (62%) led to at least one publication (92 total), while 67 (50%) resulted in conference presentations (85 total). The average research output per grant was 1.3, with costs of $12,547 per research output and $24,139 per publication. Research costs increased over time, with a slight decrease in 2019. CONCLUSIONS: GRSC-funded research consistently generates peer-reviewed knowledge, with over half of projects producing publications or presentations. Despite rising research costs, the high success rate in knowledge dissemination underscores GRSC's critical role in sustaining and advancing glaucoma research in Canada.
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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 | 0.038 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".