AN APPLE A DAY KEEPS A DOCTOR AWAY; AN APPLE CIDER VINEGAR A DAY KEEPS THE DEPRESSION AWAY
Bibliographic record
Abstract
Background: Apple cider vinegar is a natural acidic juice that has many beneficial effects, as it is a vital source of several vitamins, contains sufficient quantities of acetic acid and citric acid and trace elements which have been proved by several practical observations and hypothesis but few scientific evidences.Methodology: The model experiment is carried to investigate the Anti-depressant activity of apple cider vinegar. As it helps to improve depressed state by metabolizing the proteins into amino acids that results in creation of tryptophan that has a critical role in production of serotonin that acts as mood elevating neurotransmitter which fights against the depressed mood and gives an energetic feeling!Methodology: The experiment was carried on 3 groups of mice, each group containing 10 mice; as control, treated and standard (avg. weight 25 gm). The control group was kept on distilled water ad libitum; treated mice were on ad-libitum apple cider vinegar diluted with water in the dilution of 500mg/liter for 10 days and standard group was treated with Fluoxetine in the dose of 30mg/kg. The test method used for evaluating anti-depressant activity is Forced Swimming Test where depression was induced by forced swimming and their behavioral responses, including immobility and struggling were observed during 10 minutes.Results: the result were evaluated by one-way ANOVA followed by the Post Hoc Tukey test, Where P-value, ***p<0.001 was considered to be significant. The test results show that the treated group showed significant increase in struggling time of FST.Conclusions: Based on statistical analysis we can surly conclude that apple cider vinegar can turn down the depression and if we use it in our regular diet, then we can combat through depression which is prevalent in our society. As it showed an insignificant difference in result comparative to standard.
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 | 0.000 | 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 | 0.001 | 0.001 |
| 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".