Excerpt From PHS Guideline for Reducing HIV, HBV and HCV Transmission Through Organ Transplantation
Bibliographic record
Abstract
The intent of the PHS guideline is to improve organ transplant recipient outcomes by reducing the risk of unexpected HIV, HBV and HCV transmission, while preserving the availability of high-quality organs. An evidence-based approach was used to identify the most relevant studies and reports on which to formulate the recommendations. This excerpt from the guideline comprises (1) the executive summary; (2) 12 criteria for assessment of risk factors for recent HIV, HBV and HCV infection; (3) 34 recommendations on risk assessment (screening) of living and deceased donors; testing of living and deceased donors; informed consent discussion with transplant candidates; testing of recipients pre- and posttransplant; collection and/or storage of donor and recipient specimens; and tracking and reporting of HIV, HBV and HCV; and (4) 20 recommendations for further study. For the PHS guideline in its entirety, including the background, methodology and primary evidence underlying the recommendations, refer to the source document in Public Health Reports, accessible at http://www.publichealthreports.org/issuecontents.cfm?Volume=128&Issue=4. For more in-depth information on the evidence base, including tables of all study-level data, refer to Solid Organ Transplantation and the Probability of Transmitting HIV, HBV or HCV: A Systematic Review to Support an Evidence-Based Guideline, accessible at http://stacks.cdc.gov/view/cdc/12164/.
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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.115 | 0.060 |
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".