Applicability of vitamins in the management of COVID-19: An overview
Bibliographic record
Abstract
The pandemic situation due to COVID-19 has crippled the lives of the whole world population and has affected almost every individual in one way or the other.Researchers have been intrigued due to the increasing number of strains and symptoms.Several approaches have been used to control the spread of this highly infectious disease: early detection of the infected individual, development of a suitable drug and containment of the spread of this virus.Although, several vaccines have been developed, they have shown to have their own limitations and side-effects.One of the measures which has been adopted by the global health agencies is to educate people (infected or uninfected) regarding the maintenance of strong immune system to prevent the infection and lessen the health complications.There are several important factors which determine the immunity of an individual.Eating balanced diet and maintaining the proper supplication of nutritional components are being suggested by health experts to keep the immunity strong.Minerals and vitamins must be maintained in the diet for proper health and immunity.Vitamins have various roles in human physiology.In this review, the relevance of vitamins in the maintenance of immunity has been discussed and reviewed in prevention of adverse health effects of
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".