Retention of Alkamides in Dried<i>Echinacea</i><i>p</i><i>urpurea</i>
Bibliographic record
Abstract
Different drying methods, such as freeze-drying (FD), vacuum microwave drying (VMD), and air-drying (AD), were applied to fresh roots and leaves of Canadian-grown Echinacea purpurea to determine the optimal method for preserving alkamide levels. Using HPLC, six alkamide fractions (alkamides 1, 2, 3, 6a/6, 7, 8/9) were quantitated in dried roots, whereas four alkamide fractions (alkamides 1, 2, 3, 8/9) were measured in dried leaves. Different elution conditions used in HPLC for alkamide analysis did not affect the eluted fractions nor the quantitation of different alkamides. Individual alkamide concentrations in roots and leaves were affected by the drying methods used. To preserve higher levels of total alkamides, FD was found to be the best method, VMD was a superior method for drying roots than AD at 70 degrees C, while AD at 50 degrees C was the preferred method for drying leaves of E. purpurea.
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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 | 0.000 | 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) | 0.001 | 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 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".