Determinants of Clinician Adoption of Regenerative Therapies in the Uk and Canada: An Ophthalmology Perspective
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
The determinants of adoption of regenerative medicine therapies are currently poorly understood. This study aims to draw comparison between the UK and Canada in terms of factors likely to affect healthcare adoption of future regenerative therapies in ophthalmology. Conducting semi-structured interviews with senior ophthalmologists in the UK and Canada, their perceptions of factors either enabling or limiting adoption were recorded and analyzed. A number of key concepts were extracted from the interview data, perceived by stakeholders to contribute to adoption. The core factors developed in this work will be of use to those looking to understand the opportunities and risks involved in securing clinician adoption in both the UK and Canada.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it