A multicenter study evaluation of the <scp>ClearLLab 10C</scp> panels
Bibliographic record
Abstract
Multiparameter flow cytometry plays an important role in the diagnosis, staging, and monitoring of patients with a suspected hematological malignancy. The ClearLLab 10C Panels consist of four reagent panels (B-Lineage Tube, T-Lineage Tube, and 2 Myeloid Lineage Tubes), each consisting of 10 color/10 antibody conjugates utilizing Beckman Coulters proprietary dry format optimized for investigating patients with suspected leukemia or lymphoma. A multicenter study was conducted to evaluate the performance of the ClearLLab 10C Panels for qualitative assessment of normal versus abnormal phenotype in peripheral blood, bone marrow, and lymph node samples with suspected hematological malignancies. ClearLLab 10C was compared to laboratory developed tests (LDTs) and final clinical diagnosis. Four clinical sites were used to enroll patient's spent specimens (n = 453); three laboratories in North America and one in Europe. Of the 453 specimens, 198 had no malignancy and 255 contained an abnormal population. The diagnostic accuracy of the ClearLLab 10C Panels was achieved with sensitivity of 96% and specificity of 95% with respect to patient final clinical diagnosis. The agreement of phenotyping between ClearLLab10C Panels and LDTs was 98%. Any differences noted between ClearLLab 10C and LDT were due to either the presence of populations below the level of detection, the lack of clinical information provided to the evaluators, or marker(s) not present in these panels. Overall, the ClearLLab 10C demonstrated excellent agreement to LDTs and diagnosis. These four reagent panels can be adopted by individual laboratories to assess the presence or absence of malignancy.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".