Lost in Translation: The Gut Microbiota in Psychiatric Illness
Bibliographic record
Abstract
Despite decades of research, and many promising hypotheses, the underlying etiology and pathophysiology of psychiatric illness remains unknown. There is evidence for the involvement of the HPA axis, monoamine neurotransmitters, inflammation, early life events, and the environment, among other factors,1 but, to date, there has not been a unifying theory to connect these different lines of research. Concurrently, there has been burgeoning interest in the role the gut microbiota may play in health and disease. In fact, the gut microbiota influences many of the factors that may be involved in psychiatric illness and is shaped by early life events and environmental factors, including diet, migration, and urbanicity.2 There is now a wealth of animal studies demonstrating that the gut microbiota plays a critical role in modulating the brain and behaviour; however, to date, there has been a paucity of studies looking at the gut microbiota in psychiatric illness. Given the potential for development of preventative and therapeutic interventions targeting the microbiota, it is essential that clinical studies of the gut microbiota in psychiatric illness be performed.
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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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.124 | 0.037 |
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".