Bibliographic record
Abstract
Wine is one of the earliest alcoholic beverages ever recovered since ancient times to have received such high scientific research profile over the years. The beneficial effect it has on human health has contributed to this context. Recent studies investigated the polyphenolic compounds in red wine and they have been able to associate it with beneficial effects on reduced risk for developing cardiovascular disease when consumed moderately. Additionally, although alcohol is a known carcinogen, wine consumption may have a beneficial influence on some kinds of cancer. Resveratrol, a polyphenol occurring in wine can reduce cell recovery and stimulate the apoptotic process in leukemic and colonic cells. Moderate wine consumption is also associated with a reduced risk of type II diabetes. Red wine polyphenols have the capacity to prevent insulin resistance, inhibit hyperglycaemia and improve beta-cell function. The beneficial effects of wine consumption extend to brain health, blood pressure, bone mineral density linked to osteoporosis and bone fractures, as well as inflammation. Keywords: Alcohol, Red Wine, Phytochemicals, Polyphenols, Chronic Diseases
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 | 0.000 | 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".