MétaCan
Menu
Back to cohort

The Role of the Gut Microbiome in Cattle Production and Health: Driver or Passenger?

2020· review· en· W3008801636 on OpenAlexaff
Eóin O’Hara, A. L. A. Neves, Yang Song, Le Luo Guan

Bibliographic record

VenueAnnual Review of Animal Biosciences · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrobiomeRuminantBiologyMetagenomicsRumenBiotechnologyOmicsGut microbiomeProduction (economics)PopulationAnimal productionMicrobial ecologyHost (biology)EcologyBioinformaticsFood scienceBacteriaGeneticsPastureGeneEnvironmental healthAnimal science

Abstract

fetched live from OpenAlex

Ruminant production systems face significant challenges currently, driven by heightened awareness of their negative environmental impact and the rapidly rising global population. Recent findings have underscored how the composition and function of the rumen microbiome are associated with economically valuable traits, including feed efficiency and methane emission. Although omics-based technological advances in the last decade have revolutionized our understanding of host-associated microbial communities, there remains incongruence over the correct approach for analysis of large omic data sets. A global approach that examines host/microbiome interactions in both the rumen and the lower digestive tract is required to harness the full potential of the gastrointestinal microbiome for sustainable ruminant production. This review highlights how the ruminant animal production community may identify and exploit the causal relationships between the gut microbiome and host traits of interest for a practical application of omic data to animal health and production.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.045
GPT teacher head0.323
Teacher spread0.278 · 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 designOther design
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

Citations247
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAnnual Review of Animal BiosciencesSame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207