Bibliographic record
Abstract
Living donors are the preferred source of organs for kidney transplantation, which is the treatment modality of choice for end-stage kidney disease. Health care systems widely promote living kidney donation. However, women are consistently overrepresented among living donors. The reasons behind the sex-based disparity in living kidney donation remain poorly understood. Compared to women, men possess a greater amount of kidney function, and the higher deceased donation rate among men reflects their higher overall kidney quality. A plausible medical explanation for the sex-based disparity in living kidney donation includes an uncompromising emphasis on preserving donor health, with less emphasis placed on organ quality, which is the main criterion in deceased donor selection. On the other hand, consent to deceased donation is also greater in women, indicating their greater desire to donate even though fewer women actually become deceased donors. Therefore, nonmedical reasons for the sex disparity in living donation must be sought. Increased empathic distress or emotional memory; a greater sense of responsibility, urgency, and impulsiveness with increased reaction to empathy; a different body image; and a different social status may all contribute to greater living kidney donation in women. Economic inequity may be the singular explanation when personal worth links to economic worth. To better understand the sex disparity in living kidney donation, we need better data on the reasons behind both nondonation and donor rejection after evaluation in clinical practice. Nondirected living kidney donation provides unique opportunities to minimize factors such as emotional distress, empathy, and impulsiveness. More liberal acceptance criteria for donors with isolated medical abnormalities and testing legitimate donor reimbursement strategies based on actual income levels rather than a fixed amount can assist in both ascertaining the reasons behind the sex disparity in living kidney donation and increasing overall living kidney donation rates.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".