Meeting the transfusion needs of a patient with anti-En <sup>a</sup> requires an international effort
Bibliographic record
Abstract
Abstract This extraordinary case showcases the identification of a rare anti-En a specificity that was assisted by DNA-based red blood cell antigen typing and collaboration between the hospital blood bank in the United States, the home blood center in Qatar, the blood center Immunohematology Reference Laboratory, as well as the American Rare Donor Program (ARDP) and the International Society for Blood Transfusion (ISBT) International Rare Donor Panel. En a is a high-prevalence antigen, and blood samples from over 200 individuals of the extended family in Qatar were crossmatched against the patient’s plasma with one compatible En(a–) individual identified. The ISBT International Rare Donor Panel identified an additional donor in Canada, resulting in a total of two En(a–) individuals available to donate blood for the patient.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".