<scp>d</scp>-serine and schizophrenia: an update
Bibliographic record
Abstract
Considering the lengthy history of pharmacological treatment of schizophrenia, the development of novel antipsychotic agents targeting the glutamatergic system is relatively new. A glutamatergic deficit has been proposed to underlie many of the symptoms typically observed in schizophrenia, particularly the negative and cognitive symptoms (which are less likely to respond to current treatments). D-serine is an important coagonist of the glutamate NMDA receptor, and accumulating evidence suggests that D-serine levels and/or activity may be dysfunctional in schizophrenia and that facilitation of D-serine transmission could provide a significant therapeutic breakthrough, especially where conventional treatments have fallen short. A summary of the relevant animal data, as well as genetic studies and clinical trials examining D-serine as an adjunct to standard antipsychotic therapy, is provided in this article. Together, the evidence suggests that research on the next generation of antipsychotic agents should include studies on increasing brain levels of D-serine or mimicking its action on the NMDA receptor.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".