Bibliographic record
Abstract
PURPOSE OF REVIEW: The prevention and treatment of rejection have been the major focus of clinical and research studies since the inception of heart transplantation. Recent improvement in survival after transplant has been in large part due to continued advancement in antirejection therapies. RECENT FINDINGS: The combination of steroids/cyclosporine/azathioprine has been widely used since the early 1980s. The last decade has seen the increasing use of the drugs mycophenolate mofetil and tacrolimus. Newer agents such as target of rapamycin protein inhibitors and anti-interleukin-2 inhibitors have come under intense research recently, and may play a significant role in heart transplantation. Further study is required for agents such as rituximab. With the recent introduction of a new grading of cardiac allograft rejection, controversy remains over when rejection should be treated and which agents should be used. SUMMARY: Use of newer proven antirejection drugs has reduced rejection and improved survival after heart transplantation. Rejection and side effects from these drugs are still major problems, however; therefore continued research in this area is required.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".