Influence of gamma radiation in chestnut (Castanea sativa Mill.) vitamin E content
Bibliographic record
Abstract
Chestnut has to be postharvest treated to increase its shelf-life and to meet the fitosanitary regulations during exportation. The most common preservation method for chestnuts was the chemical fumigation with methyl bromide, a toxic agent that is under strictly use according to Montreal Protocol due to the adverse effects on human health and environment. Furthermore, its use has been prohibited by the European Union since March 2010 [1]. Food irradiation is a possible feasible alternative to substitute the traditional quarantine chemical fumigation treatment. The present study evaluates the influence of gamma irradiation in vitamin E content of chestnut. Vitamin E is a term frequently used to designate a family of related compounds, namely tocopherols and tocotrienols, which are important lipophilic antioxidants with essential effects in living systems against aging, strengthening the immune system and reduction of cancer risk, reducing viral load in HIV-infected or in the treatment of Parkinson-syndrome [2-5]. Y-tocopherol and its physiological metabolite, 2,7,8-trimethyl-2-(β-carboxyethyl)-6-hydroxychroman proved to have anti-inflammatory activity, being promising alternatives to drugs used as cyclooxygenase inhibitors, a key enzyme in the inflammatory process. Y–Tocopherol represents 95% of the vitamin E in chestnuts, which could give to this fruit a functional food classification [6].
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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) | 0.002 | 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".