Resveratrol: A New Potential Therapeutic Agent for Melanoma?
Classification
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Melanoma is the most life-threatening and aggressive class of skin malignancies. The incidence of melanoma has steadily increased. Metastatic melanoma is greatly resistant to standard antimelanoma treatments such as chemotherapy, and the 5-year survival rate of cases with melanoma who have a metastatic form of the disease is less than 10%. The contributing role of apoptosis, angiogenesis and autophagy in the pathophysiology of melanoma has been previously demonstrated. Thus, it is extremely urgent to search for complementary therapeutic approaches that could enhance the quality of life of subjects and reduce treatment resistance and adverse effects. Resveratrol, known as a polyphenol component present in grapes and some plants, has anti-cancer properties due to its function as an apoptosis inducer in tumor cells, and anti-angiogenic agent to prevent metastasis. However, more clinical trials should be conducted to prove resveratrol efficacy. Herein, for the first time, we summarize the current knowledge of anti-cancerous activities of resveratrol in melanoma.
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) | 0.001 | 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 | 0.001 |
| 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 it