Recommended curriculum for subspecialty training in transplant infectious disease on behalf of the American Society of Transplantation Infectious Diseases Community of Practice Educational Initiatives Working Group
Bibliographic record
Abstract
R. Avery, H. Clauss, L. Danziger-Isakov, J. Davis, K. Doucette, D. van Duin, J. Fishman, F. Gunseren, A. Humar, S. Husain, C. Isada, K. Julian, D. Kaul, D. Kumar, S. Martin, M. Michaels, M. Morris, F. Silveira, A. Subramanian. Recommended curriculum for subspecialty training in transplant infectious disease on behalf of the American Society of Transplantation Infectious Diseases Community of Practice Educational Initiatives Working Group.Transpl Infect Dis 2010: 12: 190–194. All rights reserved Abstract: The American Society of Transplantation Infectious Diseases (ID) Community of Practice has established an education workgroup to identify core components of a curriculum for training specialists in transplant ID. Clinical, laboratory, and research training form the triad of components on which an additional year of ID training, dedicated to the care of solid organ and hematopoietic stem cell transplant recipients, should be based. The recommended training environment would have access to adequate numbers of transplant patients, along with qualified faculty committed to teaching specialized fellows in this area. The learning objectives for both inpatient and outpatient clinical training are presented. The laboratory component requires trainees to attain expertize in utilizing and interpreting cutting-edge diagnostics used in transplant medicine. The research component may involve basic science, and translational or clinical research individualized to the trainee. Finally, suggestions for evaluation of both the fellows and the training program are provided.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.099 | 0.041 |
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".