Bibliographic record
Abstract
At present, googling the search terms "COVID-19" and "Functional foods" yields nearly 500,000,000 hits, witnessing the growing interest of the scientific community and the general public in the role of nutrition and nutraceuticals during the COVID-19 pandemic. Many compounds have been proposed as phytotherapics in the prevention and/or treatment of COVID-19. The extensive interest of the general public and the enormous social media coverage on this topic urges the scientific community to address the question of whether which nutraceuticals can actually be employed in preventing and treating this newly described coronavirus-related disease. Recently, the Canadian biotech pharma company "FSD Pharma" received the green light from the Food and Drug Administration to design a proof-of-concept study evaluating the effects of ultramicronized palmitoylethanolamide (PEA) in COVID-19 patients. The story of PEA as a nutraceutical to prevent and treat infectious diseases dates back to the 1970s where the molecule was branded under the name Impulsin and was used for its immunomodulatory properties in influenza virus infection. The present paper aims at analyzing the potential of PEA as a nutraceutical and the previous evidence suggesting its anti-inflammatory and immunomodulatory properties in infectious and respiratory diseases and how these could translate to COVID-19 care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".