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Record W4402580608 · doi:10.1016/j.pedhc.2024.06.015

Influence of Feeding Practices on Intestinal Microbiota Composition in Healthy Chinese Infants: A Prospective Cohort Study

2024· article· en· W4402580608 on OpenAlexaff
Kris Yuet Wan Lok, Jade Ll Teng, Heidi Sze Lok Fan, Yuanchao Ma, Tsz Tuen Li, Susanna K. P. Lau, Patsy Ph Chau, Hani El‐Nezami, Patrick Ip, Marie Tarrant, Hein M. Tun, Patrick C. Y. Woo

Bibliographic record

VenueJournal of Pediatric Health Care · 2024
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversity of British Columbia, Okanagan Campus
FundersHealth and Medical Research FundUniversity of Hong Kong
KeywordsBreastfeedingFormula feedingProspective cohort studyInfant feedingBreast feedingMedicineGut floraComposition (language)CohortCohort studyPediatricsNurse practitionersInternal medicineImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: This study investigates the impact of different feeding methods (direct breastfeeding, expressed milk feeding, formula feeding) on the infant microbiota at 6 weeks of age. METHODS: A total of 217 healthy infants stool samples were collected from Hong Kong between August 2018 and December 2019. RESULTS: Various microbial taxa, including the genera Enterobacter and Raoultella were identified in the expressed breast milk feeding group. The richness and composition of the major bacterial phyla showed similar abundance between direct breastfeeding and expressed breast milk. DISCUSSION: These findings suggests that these bacteria may have colonized the milk during expression or could be introduced from other external sources. The mode of breastfeeding did not significantly alter microbiota parameters in the infant gut at 6 weeks.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.375
Teacher spread0.362 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractno

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