International stem cell tourism: a critical literature review and evidence-based recommendations
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
Abstract Stem cell tourism is an emerging area of medical tourism activity. Frustrated by the slow translation of stem cell research into clinical practice, patients with debilitating conditions often seek therapeutic options that are not appropriately regulated. This review summarises recent developments in the field of stem cell tourism and provides clinicians with the information necessary to provide basic pretravel health advice to stem cell tourists. PubMed and Scopus databases were consulted for relevant publications, using combinations of the terms ‘stem cell’, ‘tourism’, ‘regenerative medicine’, ‘international’, ‘travel medicine’ and ‘environmental health’. The leading countries in the international stem cell tourism market are the USA, China, India, Thailand and Mexico. As the majority of clinics offering stem cell therapies are based in low- and-middle-income countries, stem cell tourists place themselves at risk of receiving an unproven treatment, coupled with the risk of travel-related illnesses. These clinics do not generally provide even basic travel health information on their websites. In addition to often being ineffective, stem cell therapies are associated with complications such as infection, rejection and tumorigenesis. Physicians, researchers, regulatory bodies, advocacy groups and medical educators are encouraged to work together to improve patient and physician education and address current legislative deficiencies.
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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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