Bibliographic record
Abstract
Ashgourd (Benincasa hispida) is valued for its nutritive and medicinal properties and further value addition is being attempted by fermentation process. In the present study, effect of fermentation was studied by using ashgourd as a substrate for nutrients and flavour components formation. Ashgourd fermented beverage was developed by using commercially available wet yeast and the changes in vitamins profile and flavouring compounds were evaluated after the fermentation process and it was compared with the raw ashgourd juice. Fermentation showed positive response indicating that, thiamine, riboflavin, niacin, pyridoxine and vitamin C were increased by 76µg, 7µg, 171µg, 459µg and 1.5mg respectively per 100 ml of the beverage in comparison to fresh juice. Fermentation showed many flavour components development in comparison to raw ashgourd juice and the fermentation process had a positive response on volatile component formation. Therefore fermentation improved the formation of nutritional and flavour components.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 |
| 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 teacher head, 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".