Global optometrist top 200 research ranking
Bibliographic record
Abstract
Clinical relevance Clinical optometric practice is underpinned by a rigorous research base, the primary evidence for which is publications in refereed scientific journals. Leading optometrists who publish this work should be identified and celebrated.Background This work aims to derive publication metrics of the leading optometric researchers worldwide.Methods: An extensive global search was conducted to discover leading optometric researchers; 480 names were identified. A custom-designed bibliographic search tool was developed to interrogate the Scopus database (Elsevier) and extract publication metrics using the unique Scopus Author Identifier number for each optometrist. On 13 January 2021, the full list was reduced to 200 optometrists (the ‘Top 200’) ranked by h-index – the ‘Global Optometrist Top 200 Research Ranking’. The output from the custom tool automatically updates every 24 hours and is available at www.optomrankings.com.Results The Top 200 have h-indices ranging from 20 to 67 and have published between 28 and 440 papers. Sixty one (30.5%) are women. Konrad Pesudovs has the highest h-index (67) and citations (51,193). The most prolific author is Robert Hess (442 papers). David Piñero is publishing at the fastest rate (17.6 papers per year). The Top 200 work in 13 nations, of whom 172 (86.0%) work in four nations: USA – 76 (38.0%), Australia – 43 (21.5%), UK – 41 (20.5%) and Canada – 16 (8.0%). Of the 72 institutions represented, the University of California, Berkeley, USA is home to the most Top 200 optometrists (17) and has the highest combined h-index of Top 200 optometrists (132).Conclusions The optometric profession is supported by a robust research base, prosecuted by a large international cohort of optometric researchers who publish extensively on a broad range of ophthalmic issues and whose work is highly cited. The 200 most impactful optometrists in the world are identified.
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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.074 | 0.061 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.025 |
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".