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Record W2333081327 · doi:10.2527/af.2016-0022

The nasopharyngeal microbiota in feedlot cattle and its role in respiratory health

2016· article· en· W2333081327 on OpenAlexafffund
Edouard Timsit, Devin B. Holman, Jennyka Hallewell, Trevor W. Alexander

Bibliographic record

VenueAnimal Frontiers · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Calgary
FundersAlberta Livestock and Meat AgencyUniversity of Calgary
KeywordsFeedlotBovine respiratory diseasePneumoniaBiologyRespiratory systemImmunologyMedicineInternal medicineAnimal science

Abstract

fetched live from OpenAlex

The nasopharyngeal microbiota is dynamic and changes dramatically after feedlot placement. Although microbial instability of the respiratory and digestive tracts has been linked to disease in other animals, it is not yet known how these changes impact development of pneumonia in cattle. There is, however, evidence to suggest that the structure of the nasopharyngeal microbiota of cattle is related to the development of pneumonia. Specifically, certain commensal bacteria that have been associated with improved animal health are reduced in the nasopharynx of cattle that develop pneumonia. Better understanding of the functionality of the bovine respiratory microbiota will facilitate new approaches to mitigate pneumonia and develop alternatives to antibiotics. Specifically, studies using sequencing technologies to characterize the interaction of commensal respiratory bacteria with pathogens and the host will aid in targeted approaches to develop respiratory probiotics.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.271
Teacher spread0.256 · 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 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

Citations59
Published2016
Admission routes2
Has abstractyes

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