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Record W2056191171 · doi:10.4161/gmic.29810

Emerging science of the human microbiome

2014· review· en· W2056191171 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGut Microbes · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMicropharma (Canada)
Fundersnot available
KeywordsMicrobiomeBiologyHuman microbiomeComputational biologyDiseaseHuman Microbiome ProjectGut microbiomeMetagenomicsHuman healthGeneBioinformaticsGeneticsMedicine

Abstract

fetched live from OpenAlex

The human gastrointestinal tract hosts a large number of microbial cells which exceed their mammalian counterparts by approximately 3-fold. The genes expressed by these microorganisms constitute the gut microbiome and may participate in diverse functions that are essential to the host, including digestion, regulation of energy metabolism, and modulation of inflammation and immunity. The gut microbiome can be modulated by dietary changes, antibiotic use, or disease. Different ailments have distinct associated microbiomes in which certain species or genes are present in different relative quantities. Thus, identifying specific disease-associated signatures in the microbiome as well as the factors that alter microbial populations and gene expression will lead to the development of new products such as prebiotics, probiotics, antimicrobials, live biotherapeutic products, or more traditional drugs to treat these disorders. Gained knowledge on the microbiome may result in molecular lab tests that may serve as personalized tools to guide the use of the aforementioned products and monitor interventional progress.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.019
GPT teacher head0.344
Teacher spread0.325 · 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