Non-trivial uses of melatonin: Its effects on sleep, jet lag, obesity, migraine, and gastrointestinal disorders
Bibliographic record
Abstract
Introduction and aim of the study: Melatonin consumption is steadily increasing. In this literature review, the authors intended to introduce the latest scientific evidence on the influence of the sleep hormone not only on the quality of time spent in bed and jet lag, but also to consider possible other positive impacts. Its eventual effects on headaches, gastrointestinal complaints, or obesity were analyzed. Materials and methods: The authors searched the scientific literature utilizing search engines such as Science Direct, Cochrane, PubMed, Google Scholar, and UpToDate. The literature review focused on the association of melatonin with issues such as sleep, migraines, GERD, IBS, and jet lag. Results: Most of the articles reviewed in this study highlighted the positive effects of melatonin supplementation on sleep problems and jet lag. Furthermore, many studies report that it likewise has a beneficial impact on conditions not directly related to sleep, such as obesity, GERD, IBS, or migraine. Nevertheless, the articles emphasize the need for further research to establish treatment protocols and to select an optimal dose.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".