Bibliographic record
Abstract
Molecular genetic details of the human coagulation system were among the first successes of the genetic revolution in the 1980s. This information led to new molecular diagnostic strategies for inherited disorders of hemostasis and the development of recombinant clotting factors for the treatment of the common inherited bleeding disorders. A longer term goal of this knowledge has been the establishment of gene transfer to provide continuing access to missing or defective hemostatic proteins. Because of the relative infrequency of inherited coagulation factor disorders and the availability of safe and effective alternative means of management, the application of gene therapy for these conditions has been slow to realize clinical application. Nevertheless, the tools for effective and safe gene transfer are now much improved, and we have started to see examples of clinical gene therapy successes. Leading the way has been the use of adeno-associated virus-based strategies for factor IX gene transfer in hemophilia B. Several small phase 1/2 clinical studies using this approach have shown prolonged expression of therapeutically beneficial levels of factor IX. Nevertheless, before the application of gene therapy for coagulation disorders becomes widespread, several obstacles need to be overcome. Immunologic responses to the vector and transgenic protein need to be mitigated, and production strategies for clinical grade vectors require enhancements. There is little doubt that with the development of more efficient and facile strategies for genome editing and the application of other nucleic acid-based approaches to influence the coagulation system, the future of genetic therapies for hemostasis is bright.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".