Reduction of variation in T‐cell subset enumeration among 55 laboratories using single‐platform, three or four‐color flow cytometry based on CD45 and SSC‐based gating of lymphocytes
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Enumeration of CD4(+) and CD8(+) T-cell subsets provides relevant information for diagnosis and monitoring of patients with cellular immunodeficiencies. As a result, an external quality assurance scheme was implemented in Belgium, The Netherlands, and Luxembourg in 1995. A workshop was held to train the participants in state-of-the art technology for assessment of absolute T-cell subset counts (i.e., a three or four-color, single-platform assay with lymphocyte gating based on CD45 and sideward light scatter) with the aim to achieve between-site coefficients of variation (CVs) <10% and within-site CVs <5% for > or =75% of the participants. METHODS: Three send-outs of stabilized blood from a healthy donor were distributed to 55 laboratories, each with the request to perform the standard assay on three occasions. For comparison, each laboratory performed its local technique in parallel. RESULTS: With the standard technique, between-site CVs of approximately 8% (CD3+ T cells), approximately 9% (CD4+ T cells), and approximately 10% (CD8+ T cells) were achieved. Within-site CVs were <5% for 82% (CD3+ T cells) and approximately 70% (CD4+ and CD8+ subsets) of the participants. Local techniques yielded between-site CVs of 13%-17% for CD3+, CD4+, and CD8+ T cells. CONCLUSIONS: The state-of-the-art technology for T-cell subset enumeration was implemented successfully among 55 Belgian-Dutch laboratories and resulted in significant reductions of between-site variation of absolute CD3+, CD4+, and CD8+ T-cell counts.
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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 | 0.001 |
| 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 it