Response to Chen et al and the Accompanying Commentary
Bibliographic record
Abstract
We question the decision by Transplantation to publish the article by Chen et al1 in relation to the development of liver transplantation at the Sun Yat-sen First Affiliated Hospital. Furthermore, the accompanying Commentary by Ascher and Delmonico2 provides unverified assurances that fail to acknowledge the body of evidence. As noted by the International Society for Heart and Lung Transplantation Society, “the government of the People’s Republic of China (PRC) stands alone in continuing to systematically support the procurement of organs or tissue from executed prisoners.”3 The independent China Tribunal, following strict legal protocol, concluded “absent a satisfactory explanation as to the source of readily available organs [the Tribunal] concludes that forced organ harvesting continues till today.”4 Acknowledging these grave concerns, scientific journals must exercise caution when reviewing clinical transplantation articles from China.5 Regarding the Commentary, praise for claimed reforms are based on unverified trust. However, because of persistent denials regarding any killing of prisoners of conscience6; falsified data during the supposed “reform” process7; and breaches of the dead donor rule,8 that trust has not been earned. No verifiable developments have occurred to abrogate the statement made by Francis Delmonico in June 2016 during an appearance at a Congressional hearing on organ transplant abuse in China. During an exchange, US House of Representative Chris Smith asked Francis Delmonico this question: “In 2016, how do you independently verify [Chinese government claims that there is no transplant abuse], when there has been such a backdrop of terrible duplicity, lies, and deception on the part of this government? Trust and verify; how do you do it?” Francis Delmonico responded: “I’m not an apologist. I’m not here to tell you not to worry. I’m not here to verify, that’s not my job. I’m here to say to you that there is a move within the country to change.”9 As recently as June 2021, 9 United Nations Special Rapporteurs sent joint correspondence to the Chinese Government regarding “credible evidence” of forced organ harvesting targeting minorities based on religion and/or ethnicity.10 Yet, the Commentary urges the international transplant community to have unconditional trust without any reasonable doubt. Without genuine accountability for past abuses, and transparency of current practice for review by independent auditors,11 we cannot believe claimed reforms have stopped the execution of prisoners of conscience which has fueled, and likely still fuels, China’s transplant system. Although a few bad apples may not spoil the whole barrel, sadly, we do not know which apples are good or bad in relation to the Chinese transplantation system. As transplant professionals, we must bear in mind the system we are interacting with is accused of heinous crimes against humanity involving the mass murder of innocents. Why should we believe these accusations are unfounded? China fails to adhere to the WHO Guiding Principles on Human Cell, Tissue and Organ Transplantation related to transparency (#9), traceability (#10), and openness to scrutiny (#11).12 Willful blindness and self-delusion by the international transplantation community cannot be a substitute for openness and transparency.
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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 | 0.011 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.087 | 0.067 |
| Insufficient payload (model declined to judge) | 0.024 | 0.019 |
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".