Piloting and implementation of quality assessment and quality control procedures in RBC‐Omics: a large multi‐center study of red blood cell hemolysis during storage
Bibliographic record
Abstract
BACKGROUND: The major aims of the RBC-Omics study were to evaluate the genomic and metabolomic determinants of spontaneous and stress-induced hemolysis during RBC storage. This study was unique in scale and design to allow evaluation of RBC donations from a sufficient number of donors across the spectrum of race, ethnicity, sex, and donation intensity. Study procedures were carefully piloted, optimized, and controlled to enable high-quality data collection. METHODS: The enrollment goal of 14,000 RBC donors across four centers, with characterization of RBC hemolysis across two testing laboratories, required rigorous piloting and optimization and establishment of a quality assurance (QA) and quality control (QC) program. Optimization of WBC elution from leukoreduction (LR) filters, development and validation of small-volume transfer bags, impact of manufacturing and sample-handling procedures on hemolysis parameters, and testing consistency across laboratories and technicians and over time were part of this quality assurance/quality control program. RESULTS: LR filter elution procedures were optimized for obtaining DNA for analysis. Significant differences between standard and pediatric storage bags led to use of an alternative LR-RBC transfer bag. The impact of sample preparation and freezing methods on metabolomics analyses was evaluated. Proficiency testing monitored and documented testing consistency across laboratories and technicians. CONCLUSION: Piloting and optimization, and establishment of a robust quality assurance/quality control program documented process consistency throughout the study and was essential in executing this large-scale multicenter study. This program supports the validity of the RBC-Omics study results and a sample repository that can be used in future studies.
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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) | 0.000 | 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".