Association between gut MIcrobiota, GROWth and Diet in peripubertal children from the TARGet Kids! cohort (The MiGrowD) study: protocol for studying gut microbiota at a community-based primary healthcare setting
Bibliographic record
Abstract
INTRODUCTION: The gut microbiota interacts with diet to affect body health throughout the life cycle. Critical periods of growth, such as infancy and puberty, are characterised by microbiota remodelling and changes in dietary habits. While the relationship between gut microbiota and growth in early life has been studied, our understanding of this relationship during puberty remains limited. Here, we describe the MIcrobiota, GROWth and Diet in peripubertal children (The MiGrowD) study, which aims to assess the tripartite growth-gut microbiota-diet relationship at puberty. METHODS AND ANALYSIS: The MiGrowD study will be a cross-sectional, community-based study involving children 8-12 years participating in the TARGet Kids! COHORT: TARGet Kids! is a primary healthcare practice-based research network in Canada. Children will be asked to provide a stool sample, complete two non-consecutive 24-hour dietary recalls and a pubertal self-assessment based on Tanner Stages. Anthropometry will also be conducted. The primary outcome is the association between gut microbiota composition and longitudinal growth from birth until entry into the study. Anthropometrics data from birth will be from the data collected prospectively through TARGet Kids!. Body mass index z-scores will be calculated according to WHO. The secondary outcome is the association between gut microbiota, diet and pubertal stage. ETHICS AND DISSEMINATION: Ethics approval has been obtained by the Hospital for Sick Children and St. Michael's Hospital-Unity Health, and the University of Toronto. Results will be disseminated in the public and academic sector, including participants, TARGet Kids! primary healthcare physicians teams, scientists via participation in the TARGet Kids! science and physician meetings, conferences and publications in peer-reviewed journals. The MiGrowD study results will help researchers understand the relationships underlying growth, gut microbiota and pubertal maturation in children.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".