Methods of Analysis for Anthocyanins in Plants and Biological Fluids
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Anthocyanins are the largest group of water-soluble pigments in the plant kingdom. They are responsible for most of the red, blue, and purple colors of fruits, vegetables, flowers, and other plant tissues or products. The analysis of anthocyanins is complex as a result of their ability to undergo structural transformations and complexation reactions. In addition, they are difficult to measure independently of other flavonoids, as they have similar structural and reactivity characteristics. Anthocyanins are generally extracted with weakly acidified alcohol-based solvents, followed by concentration (under vacuum), and purification of the pigments. Paper and/or thin-layer chromatography and UV-Vis spectroscopy have traditionally been used for the identification of anthocyanins. Capillary zone electrophoresis, a hybrid of chromatography and electrophoresis, is gaining popularity for the analysis of anthocyanins; however, liquid chromatography (LC) has become the standard method for identification and separation in most laboratories and may be used for both preparative and quantitative analysis. LC with mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are possibly the most powerful methods for the structural elucidation of anthocyanins available, to date. At present, the most satisfactory method for mixture analysis is the multistep method of separation, isolation, and quantification by LC with peak identification by MS and high-field NMR.
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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 | 0.000 | 0.000 |
| 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