Assessment of cord blood unit characteristics on the day of transplant: comparison with data issued by cord blood banks
Bibliographic record
Abstract
BACKGROUND: Selection of a cord blood (CB) unit for allogeneic transplantation relies on graft characterization results provided by cord blood banks (CBBs). The goal was to compare the graft characterization results obtained upon thawing and washing to those provided by CBBs at selection. STUDY DESIGN AND METHODS: With tests that assess CB graft characteristics known to impact engraftment, CB units have been analyzed after thaw and before infusion. Our results were compared to data provided by CBBs to determine the impact on engraftment and assess how CBB-supplied information can affect future CB unit selection. RESULTS: Variability was noted as to the type of information provided by the different CBBs. Also, variability was found between the information provided by CBBs and the graft characterization results obtained upon thawing and washing. In some cases, CB measures known to be predictive of engraftment were found much lower than reported by CBBs. Only the total nucleated cell count, which is the main CB graft selection criterion besides HLA matching, correlated favorably. CONCLUSIONS: Our data reveal a high degree of variability in graft characteristics provided by CBBs and often poor correlation with results obtained on thawed and washed CB units. We suggest that standardized laboratory procedures aimed at graft characterization should be used by both CBBs and transplant centers to avoid unacceptable discrepancies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".