Antibodies to Hepatitis C Virus in Kidney Transplantation
Bibliographic record
Abstract
Ninety patients on dialysis, 241 cadaveric kidney donors and 27 cadaveric kidney recipients with a follow-up of 2 years, have been investigated as for anti-HCV positivity by means of 3 tests. As for patients on dialysis and cadaveric donors, the prevalence was 32 and 4%, respectively. As for transplanted patients, it must be noted that 4 negative recipients from positive donors seroconverted, but without any change in hepatic enzymes, while in 2 or 9 anti-HCV-positive recipients, hepatic enzymes increased after transplantation. Seroconversion in patients transplanted from a negative donor was not significantly different. We conclude that, according to their experience, anti-HCV positivity in the donors is not associated with a significant risk of infection in recipients of cadaveric grafts.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".