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Record W1983198643 · doi:10.1038/srep00170

Bacterial biogeography of the human digestive tract

2011· article· en· W1983198643 on OpenAlexafffund
Jennifer C. Stearns, Michael D. J. Lynch, Dilani B. Senadheera, Howard C. Tenenbaum, Michael B. Goldberg, Dennis G. Cvitkovitch, Kenneth Croitoru, Gabriel Moreno‐Hagelsieb, Josh D. Neufeld

Bibliographic record

VenueScientific Reports · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMount Sinai HospitalWilfrid Laurier UniversityUniversity of TorontoUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsPhylumBiologyHuman microbiomeMicrobiomePhylogenetic treeZoology16S ribosomal RNABiogeographyPhylogenetic diversityHuman Microbiome ProjectOperational taxonomic unitTaxonMicrobiologyEcologyBacteriaGeneGenetics

Abstract

fetched live from OpenAlex

We present bacterial biogeography as sampled from the human gastrointestinal tract of four healthy subjects. This study generated >32 million paired-end sequences of bacterial 16S rRNA genes (V3 region) representing >95,000 unique operational taxonomic units (OTUs; 97% similarity clusters), with >99% Good's coverage for all samples. The highest OTU richness and phylogenetic diversity was found in the mouth samples. The microbial communities of multiple biopsy sites within the colon were highly similar within individuals and largely distinct from those in stool. Within an individual, OTU overlap among broad site definitions (mouth, stomach/duodenum, colon and stool) ranged from 32-110 OTUs, 25 of which were common to all individuals and included OTUs affiliated with Faecalibacterium prasnitzii and the TM7 phylum. This first comprehensive characterization of the abundant and rare microflora found along the healthy human digestive tract represents essential groundwork to investigate further how the human microbiome relates to health and disease.

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)0.000
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.249
Teacher spread0.232 · 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

Citations395
Published2011
Admission routes2
Has abstractyes

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