Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent advances have driven the development of stem cell-derived, self-organizing, three-dimensional miniature organs, termed organoids, which mimic different eye tissues including the retina, cornea, and lens. Organoids and engineered microfluidic organ-on-chips (organ chips) are transformative technologies that show promise in simulating the architectural and functional complexity of native organs. Accordingly, they enable exploration of facets of human disease and development not accurately recapitulated by animal models. Together, these technologies will increase our understanding of the basic physiology of different eye structures, enable us to interrogate unknown aspects of ophthalmic disease pathogenesis, and serve as clinically-relevant surrogates for the evaluation of ocular therapeutics. Both the burden and prevalence of monogenic and multifactorial ophthalmic diseases, which can cause visual impairment or blindness, in the human population warrants a paradigm shift towards organoids and organ chips that can provide sensitive, quantitative, and scalable phenotypic assays. In this article, we review the current situation of organoids and organ chips in ophthalmology and discuss how they can be leveraged for translational applications.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it