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Record W4293767593 · doi:10.1007/s00436-022-07610-8

Effect of rumen fluke on feed digestibility and methane emissions in sheep

2022· article· en· W4293767593 on OpenAlexfundno aff
Naomi Rutherford, J. Barley, Mark W. Robinson, Alan Gordon, T. Yan, Aurélie Aubry

Bibliographic record

VenueParasitology Research · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilQueen's UniversityAHDB Beef and LambQueen's University BelfastAgrisearch
KeywordsBiologyRumenAnimal scienceDry matterMethane emissionsForageSilageAgronomyMethaneFood scienceEcologyFermentation

Abstract

fetched live from OpenAlex

Thirty-six ewes aged 18 months were assigned to one of three groups (n = 12) on the basis of faecal egg count (FEC) for rumen fluke; C: control (FEC = 0–5 epg), T: affected (FEC ≥ 6 epg) and treated, NT: affected (FEC ≥ 6 epg) and not treated. T ewes were treated with oxyclozanide 14 days prior to the trial commencing. Ewes were fed grass silage ad libitum. Digestibility crates and respiration chambers were used to measure feed digestibility and methane production. Dry matter intake (DMI), feed digestibility and CH4/DMI did not differ (P > 0.05) between treatments. However, CH4/live weight (LW) was significantly greater (P < 0.001) for NT ewes, while that of C and T ewes were similar. This study indicates that a high rumen fluke burden can increase methane emissions but only when expressed on a body weight basis (per kg LW). As the link between rumen fluke infection and methane production has not previously been investigated within the literature, these findings demonstrate the need for further research to better understand these relationships.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.461
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.395
Teacher spread0.344 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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