Measurement of nitric oxide, nitrite and nitrate using a chemiluminescence assay:an update for the year 2000
Bibliographic record
Abstract
This review deals with the measurement of nitric oxide (NO) using the chemiluminescence assay.A preliminary discussion is offered to explain the chemical basis for this assay and emphasize the importance of measuring NO.After reviewing some practical aspects and caveats of the chemiluminescence assay, we review its application in a variety of research and clinical settings, such as measurement of breath NO and serum nitrates.The importance of avoiding confounding effects of dietary nitrates when assessing the NO system in humans is discussed and new data are provided on the confounding effects of atmospheric NO on measurement of breath NO.The utility and ease of the chemiluminescence assay for these applications is contrasted with the challenge of using chemiluminescence for correlation of vascular tone and NO production, studies in which real-time measurements are required.Although the chemiluminescence assay is one of the most reliable, rapid and reproducible assays available, it is optimal for gas phase measurements and may be suboptimal for measurement under certain circumstances.This chapter complements several more general reviews of the methodology for measuring NO.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.008 |
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".