Bibliographic record
Abstract
The only way to discover the limits of the possible is to go beyond them into the impossible. —Arthur C. Clarke As we wave goodbye to the first quarter of the 21st century, we remain humble and grateful to all we have learned from the past and continue to remain excited to see what the next quarter of this century has in store for us. In 2026, we will be celebrating the 30th anniversary of the combined Journal of Cataract & Refractive Surgery. As the current editors, we take this opportunity to pause and reflect on the leadership and vision of our founding editors Stephen Obstbaum from the United States and Emmanuel Rosen from the United Kingdom. It was the brainchild of these 2 visionaries in 1996 (following board approval from the ASCRS and ESCRS) that the European Journal of Implant and Refractive Surgery merge with the JCRS and the new JCRS became a joint scientific publication of the 2 cataract and refractive surgery societies on either side of the Atlantic, ESCRS and ASCRS. Today, our journal stands as a beacon and the “go to” source of peer-reviewed scientific information in the field of anterior segment surgery, encompassing clinical, laboratory, and experimental science in the fields of cataract, refractive, cornea, and glaucoma surgery. Scientific journal rankings are metrics that evaluate the influence, prestige, and reach of academic publications. These rankings are critical for researchers because higher-ranked journals typically have a more significant impact on the scientific community. They are also often considered more prestigious when building a professional portfolio. The well-known metrics used to rank scientific journals include the Impact Factor (IF), h-index, SCImago Journal & Country Rank, Eigenfactor score, and most recently the Altmetric score. Of these, the IF is the most widely recognized metrics for ranking scientific journals. Developed by Eugene Garfield in the 1960s, it measures the average number of citations that articles in a journal receive over a specified period, usually 2 years. The formula used to calculate the IF is as follows: Average number of citations per published paper averaged over 2 years.IFy=Citationsy−1+Citationsy−2Publicationsy−1+Publicationsy−2 Although our journal's IF in 2023 was 2.6, we were delighted when the 2024 IF scores were released. For 2024, the JCRS IF climbed to 3.2, ranking us at 17th of the 98 peer-reviewed ophthalmology journals. We are very mindful of the challenge of maintaining and further improving our IF in the scientific arena. With this in mind, we introduced a few changes in late 2024: reduced the number of original articles published per issue, introduced the Ophthalmic Images section, and encouraged randomized controlled trials, large registry studies, and big data analyses. The integration of large language models (LLMs) and artificial intelligence (AI) into scientific writing, especially in medical literature, presents both unprecedented opportunities and inherent challenges. LLMs have a transformative potential for the synthesis of information, linguistic enhancements, and global knowledge dissemination. At the same time, it raises concerns about unintentional plagiarism, the risk of misinformation, data biases, and an over-reliance on AI. Academia is at a crossroads. Although we need to harness the benefits of AI in scientific research, we also need to be very mindful of its pitfalls. In 2026, we will be publishing guidelines for reporting AI involvement in manuscript development. As a peer-reviewed journal, we need to address the challenges of AI in scientific writing, emphasizing transparency in authorship, qualification of AI involvement, and ethical considerations. Concerns regarding access equity, potential biases in AI-generated content, authorship dynamics, and accountability should be addressed. In the end, it is the human author's responsibility. We want to thank our editorial team, our publishers, the entire Editorial Board, and all our reviewers for so generously donating their valuable time to critically review manuscripts for us. We wish you all a wonderful relaxing festive season with your loved ones and a happy, healthy, and prosperous 2026. Sathish Srinivasan, FRCSEd, FRCOphth, FACS, FEBOS-CR(Hon) William J. Dupps Jr, MD, PhD Thomas Kohnen, MD, PhD, FEBO Liliana Werner, MD, PhD
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".