METHOD VALIDATION STUDY TO EVALUATE THE ANALYTICAL PERFORMANCE OF THE STAT–SITE METER FOR THE MEASURMENT OF SERUM BETA-HYDROXYBUTRATE
Bibliographic record
Abstract
Objectives To evaluate the analytical performance of the STAT-Site meter (Stanbio laboratory USA) for the measurement of serum beta-hydroxybutyrate (? OH-B) concentration. Methods The precision was evaluated using two levels of quality control materials (low and high). Within run and between run precision studies were performed. CVs (coefficient of variation) compared against accepted standards. Fifty-one leftover patient samples with previously reported ? OH-B concentrations were used for the method comparison. The accuracy was evaluated and compared to our current laboratory method, (Wako Autokit 3-HB, Wako chemical USA). Slope, intercept, correlation coefficient, Deming regression and paired t-test were calculated using Analyse-it® software Results The meter showed reasonable precision for the measurement of ? OH-B with CV of 0.0% and 6% for within run precision study and 8.82% and 10.07% for between run precision study which are acceptable according to two CAP surveys. Further these are comparable to our current method CV and the manufacturer claimed CV’s. Deming regression analysis showed a linear relationship between the two methods The slope of the regression equation was 0.98 (95% CI, 0.87-1.08); intercept 0.10 (95% CI 0.03-0.16) and correlation coefficient of 0.979.There was no bias detected by the visual inspection of the difference plot, this was confirmed by the calculation of the paired t-test (p = 0.19). Conclusion The STAT-Site meter is a practical, rapid method with wide analytical range that meets precision and accuracy criteria. The method is suitable for the use in a research context until it gets approval for clinical use.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| 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".