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Record W2289171434 · doi:10.1139/cjm-2015-0814

Faecal bacterial composition in dairy cows shedding <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i> in faeces in comparison with nonshedding cows

2016· article· en· W2289171434 on OpenAlexvenueno aff
Marija Kaevska, Karel Sedlář, Iva Bartejsova, Alena Králová, Iva Slaná

Bibliographic record

VenueCanadian Journal of Microbiology · 2016
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsnot available
Fundersnot available
KeywordsParatuberculosisBiologyFecesRuminococcusMicrobiologyMycobacterium16S ribosomal RNAHerdVeterinary medicineBacteriaAnimal scienceMedicine

Abstract

fetched live from OpenAlex

The aim of this study was to determine possible differences in the faecal microbiota of dairy cows infected with Mycobacterium avium subsp. paratuberculosis (Johne's disease) in comparison with noninfected cows from the same herds. Faecal samples from cows in 4 herds were tested for M. avium subsp. paratuberculosis by real-time PCR, and faecal bacterial populations were analysed by 454 pyrosequencing of the 16S rRNA gene. The most notable differences between shedding and nonshedding cows were an increase in the genus Psychrobacter and a decrease in the genera Oscillospira, Ruminococcus, and Bifidobacterium in cows infected with M. avium subsp. paratuberculosis. The present study is the first to report the faecal microbial composition in dairy cows infected with M. avium subsp. paratuberculosis.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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