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Record W287057585 · doi:10.1089/fpd.2013.1621

Are Super-Shedder Feedlot Cattle Really Super?

2014· article· en· W287057585 on OpenAlexafffund
Krysty Munns, Lorna Selinger, Kim Stanford, L. Brent Selinger, Tim A. McAllister

Bibliographic record

VenueFoodborne Pathogens and Disease · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsAgriculture Food and Rural DevelopmentAgriculture and Agri-Food CanadaUniversity of Lethbridge
FundersGenome AlbertaAlberta Livestock and Meat Agency
KeywordsFeedlotPulsed-field gel electrophoresisFecesBiologyVeterinary medicineAnimal scienceMicrobiologyGeneticsMedicine

Abstract

fetched live from OpenAlex

The objective of this study was to determine the frequency and duration of super-shedding in cattle by enumerating Escherichia coli O157:H7 in feces and to compare lineage and pulsed-field gel electrophoresis (PFGE) subtypes from super- and low-shedders. E. coli O157:H7 was enumerated from fecal samples obtained from the rectums of 400 feedlot cattle. Super-shedding steers (N=11) were identified, transported, and penned individually. Freshly voided fecal pats were sampled 2 h before and 6 h after feeding for 7 d, then once daily for an additional 19 d. Isolates (N=126) were subtyped using PFGE, and lineage was typed using a lineage-specific polymorphism assay. Of the 11 super-shedders identified at the commercial feedlot, only five were confirmed as super-shedders at the research feedlot, with no super-shedders identified 6 d after sampling at the commercial feedlot. Super-shedding was not consistent in fecal pats collected from the same individual at different times of the day. Isolates exhibited three distinct PFGE subtypes, with most isolates (97.6%) displaying the same subtype, including those obtained from steers that transitioned from super- to low-shedding. The short duration of super-shedding and its lack of continuance suggest that these individuals may not play as great a role in the dissemination of E. coli O157:H7 within the feedlot as previously proposed.

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)0.001
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 score0.428
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.250
Teacher spread0.238 · 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

Citations24
Published2014
Admission routes2
Has abstractyes

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