MétaCan
Menu
← Back to cohort
Record W4381248183 · doi:10.1128/spectrum.00614-23

Birth Mode Does Not Determine the Presence of Shared Bacterial Strains between the Maternal Vaginal Microbiome and the Infant Stool Microbiome

2023· article· en· W4381248183 on OpenAlexafffund
Scott J Dos Santos, Ishika Shukla, Janet E. Hill, Deborah Money, K.S. Joseph, Julie E. van Schalkwyk, Arianne Albert, Chelsea Elwood, Soren Gantt, Kirsten Grabowska, Jennifer A. Hutcheon, Matthew G. Links, Amee R. Manges, Sheona Mitchell‐Foster, Tim Dumonceaux, Zoë G. Hodgson, Janet Lyons

Bibliographic record

VenueMicrobiology Spectrum · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsWomen's Health Research InstituteUniversity of British ColumbiaUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsMicrobiomeDysbiosisBiologyVaginal deliveryHuman microbiomeTransmission (telecommunications)PregnancyObstetricsMedicineGenetics

Abstract

fetched live from OpenAlex

The importance of the gut microbiome in human health and disease is widely recognized, and there has been a growing appreciation that alterations in gut microbiome composition during a "critical window" of development may impact health in later life. Attempts to correct gut microbiome dysbiosis related to birth mode are underpinned by the assumption that the lack of exposure to maternal vaginal microbes during caesarean delivery is responsible for dysbiosis. Here, we demonstrate that there is limited transmission of the maternal vaginal microbiome to the neonatal gut, even in cases of vaginal delivery. Furthermore, the presence of identical strains shared between mothers and infants in early life, even in cases of caesarean delivery, highlights compensatory microbial exposures and sources for the neonatal stool microbiome other than the maternal vagina.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.249
Teacher spread0.239 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueMicrobiology Spectrum→Same topicGut microbiota and health→French-language works237,207→