Bibliographic record
Abstract
Objective: To compare the scientific content of recent general media articles on tryptophan, diet and depression, with recent empirical research into dietary manipulation of tryptophan published in the scientific literature. Method: A review of the recent empirical research into the role of tryptophan in depression, focusing on dietary methods to influence tryptophan levels. In parallel, a review of recent articles in the general English language media regarding tryptophan and mood. Results: Empirical evidence for improving mood through dietary manipulation of tryptophan is lacking, and it is difficult to change plasma tryptophan levels through diet alone. Tryptophan supplementation and depletion studies suggest that altering tryptophan levels may only benefit certain groups of patients who have a personal or family history of depression. Scientific studies also focus on elucidating mechanisms in depression, rather than treating depression by changing tryptophan levels. However, general media articles often recommend diets and foods to increase blood tryptophan levels and raise brain serotonin levels. Such recommendations are not supported by scientific studies. Conclusion: It is very difficult to alter blood tryptophan levels through dietary methods alone, outside of a laboratory or research setting. Only a small number of lay articles provide sound advice, with general media reports on tryptophan often being hyperbolic and misleading. A clinician should be aware of the type of (mis)information a patient may have accessed and have the scientific knowledge to explain the impracticalities of influencing tryptophan levels through diet alone.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".