Evaluation of cell population data on the UniCel DxH 800 Coulter Cellular Analysis system as a screening for viral infection in children
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: The utility of WBC cell population data (CPD) for the differential diagnosis of viral infection from normal control, bacterial infection, and tuberculosis in children was investigated. METHODS: A data set of 602 total whole-blood samples were analyzed on the DxH 800 System for complete blood cell count (CBC) with leukocyte differential from children with the following sample breakdown: 77 confirmed diagnoses of viral infections (Epstein-Barr virus; 30, influenza A; 19, rota virus; 11, other viruses;17), 54 normal control, 71 bacterial infection, 17 TB patients, and 383 with various diseases. The mean (MN) and standard deviation (SD) of the volume (V), conductivity (C), five light-scatter measurements, and 14 calculated parameters were obtained for the leukocytes. RESULTS: Using a combination of the CBC and CPD parameter values, a decision rule, composed of 21 parameters, for the screening of viral infection in children was developed. Using this decision rule, 74 of 77 (96.1%) viral infections, two of 54 (3.7%) normal samples, one of 17 (5.9%) TB, and six of 71 (8.5%) bacterial infection samples were identified. The sensitivity was 96.1%, and specificity for normal control was 96.3% with an overall specificity of 93.7%. Fifty-nine samples of 383 samples (15.4%) collected from in-patient children with various diseases without confirmation of viral infection were included in this decision rule. CONCLUSION: In conclusion, the implementation of leukocytes CPD parameters can be useful in the detection of viral infection in children.
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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 | 0.008 | 0.002 |
| 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 it