ArticleSe pu = Chinese journal of chromatography2026
[Application of accuracy profile-based evaluation in the development of quantitative methods for urinary phenol detection].
Article in Se pu = Chinese journal of chromatography, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
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Authors and funding
9 authors.
Funding
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Abstract
Accurate and reliable analytical methods are fundamental to ensuring the validity and reproducibility of scientific results, particularly in research involving trace-level contaminants in biological samples. While standardized methods regulated by official guidelines are commonly used in certified laboratories, research laboratories often rely on in-house or self-developed non-standard methods tailored for specific studies. These methods, however, frequently lack harmonized validation criteria, especially regarding accuracy evaluation. Traditionally, method accuracy is assessed through single performance indicators such as recovery, relative standard deviation (RSD), or bias. These indicators, although useful, may vary widely in their interpretation and offer limited insight into overall method performance, particularly when comparing between laboratories or over different concentration ranges. To address these limitations, the Société Française des Sciences et Techniques Pharmaceutiques (SFSTP) introduced the accuracy profile approach. This method integrates both trueness and precision using a statistical model to generate
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Registered trials
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