Bioactive substances in leaves of two amaranth species,<i>Amaranthus tricolor</i>and<i>A. hypochondriacus</i>
Bibliographic record
Abstract
Khanam, U. K. S. and Oba, S. 2013. Bioactive substances in leaves of two amaranth species, Amaranthus tricolor and A. hypochondriacus. Can. J. Plant Sci. 93: 47–58. Bioactive substances and phenolic contents of Amaranthus tricolor and A. hypochondriacus leaves were evaluated using four cultivars of each species. Leaf colour attributes (L*, a* and b*) and betacyanins varied widely among the cultivars. The a* value, betacyanins and betaxanthins, appeared to be rich in A. tricolor, whereas betxanthins were twofold higher in A. hypochondriacus. Isoqercetin and rutin were the most abundant flavonoids in all amaranth cultivars. Hyperoside was found only in the A. hypochondriacus cultivar New Aztec. Salicylic acid, syringic acid, gallic acid, vanilic acid, ferulic acid, p-coumaric acid and sinapic acid were the most common phenolic acids in all amaranth cultivars. Significant amounts of ellagic acid and sinapic acid were detected in A. hypochondriacus cultivars. Total phenol content (TPC) was found to be strikingly greater than total phenol index (TPI) in A. tricolor than in A. hypochondriacus. All the amaranth cultivars showed a high correlation between total antioxidant activity and total phenol content.
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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) | 0.000 | 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 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".