Acute tryptophan depletion in humans: a review of theoretical, practical and ethical aspects
Bibliographic record
Abstract
The acute tryptophan depletion (ATD) technique has been used extensively to study the effect of low serotonin in the human brain. This review assesses the validity of a number of published criticisms of the technique and a number of previously unpublished potential criticisms. The conclusion is that ATD can provide useful information when results are assessed in conjunction with results obtained using other techniques. The best-established conclusion is that low serotonin function after tryptophan depletion lowers mood in some people. However, this does not mean that other variables, altered after tryptophan depletion, are necessarily related to low serotonin. Each aspect of brain function has to be assessed separately. Furthermore, a negative tryptophan depletion study does not mean that low serotonin cannot influence the variable studied. This review suggests gaps in knowledge that need to be filled and guidelines for carrying out ATD studies.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".