Effect of Grinding the Herb and Boiling the Infusion on Total Phenolic Content and Antioxidant Capacity of Herbal Infusions
Bibliographic record
Abstract
Herbal infusions are one of the most consumed beverages in the world. The object of this work was to estimate the phenolic content and evaluate the antioxidant capacity of Cumin seeds (Cuminum cyminum L.) and Anise seeds (Pimpinella anisum L.) infusions, and study the effect of grinding the herb and boiling the infusion on that. The total phenolic content (TPC) was determined by Folin-Ciocalteu method, and the antioxidant capacity was evaluated by two methods, DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay and FRAP (ferric reducing antioxidant power) assay. The TPC and antioxidant activity have increased by grinding the herb and boiling the infusion. By grinding, the TPC and antioxidant activity have nearly multiplied.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".