Implementation of a gene therapy education initiative by the ASGCT and Muhimbili University of Health and Allied Sciences
Bibliographic record
Abstract
There has been rapid growth in gene therapy development with an expanding list of approved clinical products. Several therapies are particularly relevant to patients in low- and middle-income countries. Moreover, investing in research and manufacturing presents an opportunity for economic development. To increase awareness of gene therapy, the American Society of Gene and Cell Therapy partnered with the Muhimbili University of Health and Allied Sciences, Tanzania, to create a certificate-bearing course. The goal was to provide faculty teaching in graduate and medical schools with the tools needed to add gene therapy to the university curriculum. The first virtual course was held in October of 2022, and 45 individuals from 9 countries in Africa completed the training. The content was new to approximately two-thirds of participants, with the remaining third indicating that the course increased their knowledge base. The program was well received and will be adapted for other under-resourced regions.
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 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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.136 | 0.088 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".