Bibliographic record
Abstract
Introduction French and British researchers have treated X-linked severe combined immune deficiency syndrome (X-SCID), otherwise known as “bubble boy” disease. Italian and UK researchers have also treated a related disease, ADA-SCID. Though only three patients were enrolled in the study, Swiss and German researchers have treated yet another severe immune disorder, chronic granulomatous disease. And some commentators believe American researchers are on the cusp of a durable treatment for hemophilia B. In these instances, it would appear that gene transfer – briefly, the administration of genetic materials to human beings – has finally earned the title of gene therapy . But the field's development has been, and continues to be, a long, strange trip. As I write, the most visible name associated with gene transfer, W. French Anderson, is serving a fourteen-year prison sentence on child molestation charges. Another leading figure, James Wilson, has nearly finished a five-year, FDA-imposed ban on leading clinical studies. Other sanctions in the field's thirty-year history include one of the earliest ever violations of rules for human research issued by the US Department of Health and Human Services (Martin Cline, for initiating a study without proper IRB review), and a widely publicized rebuke of two other leading figures (Ronald Crystal and Jeffrey Isner) for not reporting trial deaths to the NIH. In 1995, a high-level panel at the NIH faulted the field for rushing into clinical trials. 5 In 2000, two prominent researchers editorialized in the pages of Science magazine “gene therapy has many of the worst examples of clinical research that exist.”
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.035 |
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".