Novel Coronavirus Disease Pandemic and Ophthalmologists Perspectives
Bibliographic record
Abstract
Ophthalmologists are among those healers facing a higher risk of acquiring novel coronavirus disease 2019, called COVID-19, during their professional duties since they have close physical contact with their patients. Some patients with COVID-19 may present with or may develop conjunctivitis during the course of the illness. The ocular secretions and tears have been identified to have positive results to COVID-19 tests and as such could be a source of spread. This review aims at providing the useful guidelines to ophthalmic professionals for their own safety, and safety of their patients based on the available current literature, and also based on personal experience and observations. Literature search was made on PubMed for COVID-19 in relation to ophthalmology in the limited period of the last quarter of 2019 and first quarter of 2020. Research also included access to current guidelines published by various ophthalmic societies. Accordingly, present and future ophthalmic practice patterns need to be modified.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".