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Record W2790323868 · doi:10.1128/msphere.00017-18

Air-Dried Brown Seaweed, <i>Ascophyllum nodosum</i> , Alters the Rumen Microbiome in a Manner That Changes Rumen Fermentation Profiles and Lowers the Prevalence of Foodborne Pathogens

2018· article· en· W2790323868 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

VenuemSphere · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAcadian Seaplants (Canada)Agriculture Food and Rural DevelopmentAgriculture and Agri-Food CanadaUniversity of Alberta
Fundersnot available
KeywordsRumenAscophyllumBiologyFermentationFecesPopulationMicrobiomeFood scienceButyrateMicrobiologyAnimal scienceBotanyAlgae

Abstract

fetched live from OpenAlex

Maintaining product safety and reducing the carbon footprint of production are two sustainability goals of the livestock industry. The objective of this study was to study the impact of Tasco, a product derived from the brown macroalga Ascophyllum nodosum , on the rumen microbiome and its function. The inclusion of Tasco altered both rumen and fecal microbiota levels without affecting rumen fermentation. Tasco reduced fecal Escherichia coli populations and specifically reduced the prevalence of Shiga toxin-producing E. coli O45, O103, O111, and O121 in feces. The findings of this study highlight the application of Tasco as a potential feed additive to reduce pathogen shedding in rams without interfering with ruminal metabolism.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.235

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 head0.019
GPT teacher head0.221
Teacher spread0.201 · 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