21st century citation analysis of the field of contact lenses
Bibliographic record
Abstract
Clinical relevance: The scientific foundations for clinical contact lens practice are rooted in the ophthalmic literature. This analysis of contact lens papers celebrates contemporary research achievements in the contact lens field.Background: This work aims to assemble contact lens-related publication metrics so as to identify the most impactful papers published so far this century, as well the top countries, authors, institutions and journals.Methods: A search was undertaken of the titles of papers on the Scopus database to identify contact lens-related articles published this century. The ten most highly cited papers were determined from the total list of 4,164 papers found. Rank-order lists by count were assembled for the ‘top 25ʹ in each of four categories: authors, institutions, countries and journals. A 20-year subject-specific contact lens h-index (hCL-20-index) was derived for each author, institution, country and journal to serve as a measure of impact in the field. The top 10 constituents (of the top 25) of each category were ranked by hCL-20-index and tabulated for consideration.Results: The most highly cited paper this century is entitled ‘Soft contact lens polymers: An evolution’, by Nicholson and Vogt. Lyndon Jones is the most impactful author, with a hCL-20-index of 32. The University of New South Wales (Australia) produces the most impactful contact lens-related papers, and the United States is the most highly-ranked country. Optometry and Vision Science is the most impactful journal in the contact lens field.Conclusions: Contact lens materials and lens-associated keratitis are topics of high interest in the contemporary contact lens literature, with an emerging interest in orthokeratology for myopia control and glucose monitoring. Impactful 21st century authors, institutions, countries and journals are identified. Optometry is revealed as the leading profession in relation to the publication of impactful contact lens-related papers.
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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 | 0.011 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.111 | 0.122 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".