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Record W2848078396 · doi:10.1128/aem.00914-18

Mediation Analysis as a Means of Identifying Dietary Components That Differentially Affect the Fecal Microbiota of Infants Weaned by Modified Baby-Led and Traditional Approaches

2018· article· en· W2848078396 on OpenAlexaboutno aff
Claudia Leong, Jillian J. Haszard, Blair Lawley, Anna Otal, Rachael W. Taylor, Ewa A. Szymlek‐Gay, Elizabeth Fleming, Lisa Daniels, Louise J. Fangupo, Gerald W. Tannock, Anne‐Louise M. Heath

Bibliographic record

VenueApplied and Environmental Microbiology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsWeaningMicrobiomeGut floraGut microbiomeBiologyFecesMediationBioinformaticsImmunologyEcologyAnimal science

Abstract

fetched live from OpenAlex

The introduction of solid foods (complementary feeding or weaning) to infants leads to more-complex compositions of microbial communities (microbiota or microbiome) in the gut. In baby-led weaning (BLW), infants are given only finger foods that they can pick up and feed themselves-there is no parental spoon-feeding of puréed baby foods-and infants are encouraged to eat family meals. BLW is a new approach to infant feeding that is increasing in popularity in the United States, New Zealand, the United Kingdom, and Canada. We used mediation modeling, commonly used in health research but not in microbiota studies until now, to identify particular dietary components that affected the development of the infant gut microbiota.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.218
Teacher spread0.191 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations57
Published2018
Admission routes1
Has abstractyes

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