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Record W2999774945 · doi:10.1093/femsec/fiz203

Investigating temporal microbial dynamics in the rumen of beef calves raised on two farms during early life

2020· article· en· W2999774945 on OpenAlexafffund
Eóin O’Hara, D.A. Kenny, Emily McGovern, C.J. Byrne, Matthew S. McCabe, Le Luo Guan, Sinéad M. Waters

Bibliographic record

VenueFEMS Microbiology Ecology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaTeagasc
KeywordsBiologyRumenColonisationWeaningAnimal scienceMicrobiomeAmplicon sequencingMicrobial ecologyMicrobial population biologyBacteriaColonizationMicrobiologyFood science16S ribosomal RNAFermentationBioinformatics

Abstract

fetched live from OpenAlex

Manipulation of the rumen microorganisms during early life has emerged as a promising strategy for persistent improvement of nutrient utilisation and lowering of enteric methanogenesis. However, limited understanding of the dynamics of rumen microbial colonisation has prevented the identification of the optimum timeframe for such interventions. The present study used DNA amplicon sequencing of the 16S rRNA gene to assess bacterial and archaeal dynamics in the rumen digesta of beef calves raised on two farms from birth through to post-weaning. The colonisation patterns of both communities were influenced by age (P < 0.05) and farm of origin (P < 0.05). The bacterial community exhibited an age-wise progression during the first month of life which appeared to be partly related to diet, and settled by day 21, indicating that this may mark the boundary of a timeframe for intervention. The archaeal community appeared less sensitive to age/diet than bacteria in the first month of life but was more sensitive to farm environment. These data show that ruminal microbial composition during early life is driven by calf age, diet and local environment, and provide important fundamental information concerning the ontogeny of the rumen microbiota from birth.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.224
Teacher spread0.202 · 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 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

Citations52
Published2020
Admission routes2
Has abstractyes

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