Professional Regulation: A Potentially Valuable Tool in Responding to “Stem Cell Tourism”
Bibliographic record
Abstract
The growing international market for unproven stem cell-based interventions advertised on a direct-to-consumer basis over the internet (''stem cell tourism'') is a source of concern because of the risks it presents to patients as well as their supporters, domestic health care systems, and the stem cell research field.Emerging responses such as public and health provider-focused education and national regulatory efforts are encouraging, but the market continues to grow.Physicians play a number of roles in the stem cell tourism market and, in many jurisdictions, are members of a regulated profession.In this article, we consider the use of professional regulation to address physician involvement in stem cell tourism.Although it is not without its limitations, professional regulation is a potentially valuable tool that can be employed in response to problematic types of physician involvement in the stem cell tourism market. Stem Cell ReportsProfessional Regulation and ''Stem Cell Tourism''
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.107 | 0.021 |
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".