Standardization of <scp>CD</scp>62P measurement: results of an international comparative study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Despite long being a mainstay in describing platelet activation via degranulation, interlaboratory variation remains an issue in measurement of membrane CD62P by flow cytometry. Our objective was to identify actions that may minimize this variation. MATERIALS AND METHODS: Sixteen laboratories participated in an international comparative study. Two sets of platelet samples were prepared in one laboratory. Set 1 was stained and fixed; set 2 was fixed and required staining at participating laboratories. A single-staining method was used, and platelet populations were selected based on forward scatter/side scatter characteristics. Calibration beads were used to standardize measurement across different instruments. RESULTS: There was a large discrepancy in reported CD62P values among study sites [interlaboratory coefficient of variance (CV): 36-78%]. When electronic data were re-analysed by a single analyst using a consistent gating strategy and a stable reference point, variation decreased markedly (CV < 12%), indicating a problem with isotype control samples, possibly related to sample fixation or shipment. CONCLUSION: Consensus regarding gating strategies and use of a reliable reference point would greatly improve agreement in interlaboratory CD62P measurement.
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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 | 0.084 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".