<i>Castanea sativa</i> male flower extracts as an alternative additive in the Portuguese pastry delicacy “pastel de nata”
Bibliographic record
Abstract
Replacing artificial additives by natural compounds is a current trend in the food industry. In addition to their preserving effect, naturally obtained ingredients often exhibit important levels of bioactivities. Generally, plant species represent better sources of natural ingredients, since their compounds are less prone to causing unpleasant taste or odour. Chestnut male flower (CMF) was reported to have high antioxidant and antimicrobial activities. Hence, it was tested as an alternative to potassium sorbate in the most treasured Portuguese delicacy: "pastel de nata". Different nutritional, chemical, physical and bioactive parameters were compared in two different periods: baking day and two days after baking. All samples presented similar nutritional and chemical profiles, but those added with CMF revealed higher contents of reducing agents and radical scavengers. Accordingly, the newly obtained formulation is expected to have better effects on consumers' health, maintaining the chemical characteristics, besides rendering a novel, economically profitable, application to CMF.
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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".