Glucagon‐like peptide‐1 receptor agonists and the risk of nonarteritic anterior ischaemic optic neuropathy: A systematic review and meta‐analysis of observational studies
Bibliographic record
Abstract
Ronald M. Goldenberg has received research support and/or personal fees from AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, HLS Therapeutics, Janssen, Merck, Novo Nordisk, Sanofi. Ronnie Aronson has received research support and/or advisory and speaking fees from Abbott, Bayer, Dexcom, Eli Lilly, Insulet, Janssen, Novo Nordisk and Senseonics. Jill Trinacty has received research support and/or advisory and speaking fees from Amgen, Abbott, CCRN, CME Away, CPD, Dexcom, Eli Lilly, HLS Therapeutics, Humber River Hospital, Janssen, Novo Nordisk and Tandem. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/dom.70013. Data sharing is not applicable to this article as no new data were created or analysed in this study. Data S1. Supporting Information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".