Protocol for a systematic review on the role of the gut microbiome in paediatric neurological disorders
Bibliographic record
Abstract
INTRODUCTION: The gut-brain axis refers to the bidirectional communication that occurs between the intestinal tract and central nervous system (CNS). Through a series of neural, immune, endocrine, and metabolic signalling pathways, commensal microbiota are able to influence CNS development and neurological function. Alterations in gut microbiota have been implicated in various neuropathologies. The purpose of this review is to evaluate and summarise existing literature assessing the role of specific bacterial taxa on the development of neurodevelopmental, neuropsychiatric, and neurodegenerative pathologies of childhood. We will also discuss microbiota-based therapies dietary interventions and their efficacy. METHODS AND ANALYSIS: We will search PubMed, Cochrane Library, and OVID electronic databases for articles published between January 1980 and February 2021. A search method involving two rounds of reviewing the literature using a three-step method in each round will be performed. Two researchers will be selected, and screen titles and abstracts independently. The full text of selected articles will be assessed against inclusion criteria. Data will be extracted and evaluated using the appropriate Critical Appraisal Skills Programme (CASP) checklist. ETHICS AND DISSEMINATION: Findings from this study will be shared across relevant paediatric neurology and gastroenterology societies and submitted for peer review. This study did not require institutional ethics approval.
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 | 0.058 | 0.098 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.018 | 0.013 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.102 | 0.012 |
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".