Interference of ascorbic acid with chemical analytes
Bibliographic record
Abstract
BACKGROUND: Ascorbic acid can interfere with methodologies involving redox reactions, while comprehensive studies on main chemistry analysers have not been reported. We therefore attempted to determine the interference of ascorbic acid with analytes on the Beckman Synchron LX20. METHODS: Various concentrations of ascorbic acid were added to serum, and the serum analytes were measured on the LX20. RESULTS: With a serum ascorbic acid concentration of 12.0 mmol/L, the values for sodium, potassium, calcium and creatinine increased by 43%, 58%, 103% and 26%, respectively (P<0.01). With a serum ascorbic acid concentration of 12.0 mmol/L, the values for chloride, total bilirubin and uric acid decreased by 33%, 62% and 83%, respectively (P<0.01), and were undetectable for total cholesterol, triglyceride, ammonia and lactate. There was no definite influence of ascorbic acid on analytical values for total CO(2), urea, glucose, phosphate, total protein, albumin, amylase, creatine kinase, creatine kinase-MB, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, total iron, unbound iron-binding capacity or magnesium. CONCLUSIONS: Ascorbic acid causes a false increase in sodium, potassium, calcium and creatinine results and a false decrease in chloride, total bilirubin, uric acid, total cholesterol, triglyceride, ammonia and lactate results.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".