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Record W2333015996 · doi:10.2527/af.2016-0017

Gut microbiome and omics: a new definition to ruminant production and health

2016· article· en· W2333015996 on OpenAlexafffund
Nilusha Malmuthuge, Le Luo Guan

Bibliographic record

VenueAnimal Frontiers · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Alberta
FundersAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaAlberta Livestock and Meat Agency
KeywordsOmicsRuminantMicrobiomeBiologyGut floraMetagenomicsPhenotypeMicrobial ecologyGut microbiomeComputational biologyBiotechnologyBioinformaticsBacteriaGeneticsEcologyImmunologyGene

Abstract

fetched live from OpenAlex

Mammalians are considered as “superorganisms” due to the presence of dense and dynamic microbiota in the digestive tract that perform a wide range of metabolically, immunologically, and physiologically crucial tasks. The composition and functions of gut microbiota have been studied using “omics” based approaches without isolation and cultivation of microbes. Omics have been used in defining host phenotypes, such as susceptibility to diseases in humans. In-depth analyses of the ruminant gut microbiome (rumen and lower gut) using “omics” will help identifying microbial biomarkers that may define production and health phenotypes/susceptibility to diseases in the future.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0070.008
Science and technology studies0.0010.010
Scholarly communication0.0100.008
Open science0.0010.006
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.257
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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations52
Published2016
Admission routes2
Has abstractyes

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