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Record W4402540778 · doi:10.1093/jas/skae234.265

79 Microbiological effects of control measures during pork production

2024· article· en· W4402540778 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolism and Applications
Canadian institutionsUniversity of LethbridgeAgriculture and Agri-Food Canada
Fundersnot available
KeywordsProduction (economics)Food scienceControl (management)BiotechnologyAnimal scienceEnvironmental scienceBiologyComputer scienceEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The objective of this study was to determine the prevalence of Shiga toxin-producing Escherichia coli (STEC) O157:H7 and efficacy of control measures at a pork processing facility. Outbreaks of E. coli O157:H7 associated with pork, though not common globally, have been reported multiple times in recent years in Alberta. Sampling at a commercial facility processing hogs was carried out at monthly intervals for 11 mo. At the facility, the dressed carcasses are sprayed with 5% lactic acid (LA) and immediately air-chilled after the LA spray. At each sampling time, 14 different types of samples were collected: dirt from the holding pen floor (n = 2), gloves of workers (n = 5), scalding water (n = 1), tonsils (n = 5), cecal material (n = 5), five swabs each from hides of animals after bleeding (HAB), and carcasses after scalding (CAS), before evisceration (CBE), after evisceration (CAE), before LA spray (BLA), after LA spray (ALA), 1h after LA spray (ALA1), 2h after LA spray (ALA2), and after chilling (ACH). All samples were enumerated for total plate count (TPC), Enterobacteriaceae, and E. coli using specific media for each. In addition, an aliquot of each sample was enriched and tested for the presence of the O-antigen gene (rfbE) for E. coli O157 and Shiga toxin-producing gene (stx1/stx2) using real-time PCR. Cultures positive for both rfbE and stx were further plated for the isolation of E. coli O157:H7. Of the 683 enrichment cultures, 12 were positive for both marker genes, from cecal material (n = 2), dirt (n = 4) and HAB (n = 6). However, none of these samples yielded STEC O157 isolates. Of these enrichment cultures, 69, 45 and 32 were positive for stx1, stx2, and both stx genes, respectively. Positive samples were mostly associated with HAB, cecal material and dirt. HAB was most and least contaminated in August/June and December, differing by 1 log unit for TPC (P < 0.05). Enterobacteriaceae and E. coli on HAB were also affected by month of sampling (P < 0.05), but this temporal trend differed from TPC (Table). The numbers for TPC, Enterobacteriaceae, and E. coli all decreased (P < 0.05) as the stage of carcass processing progressed. The overall reduction of TPC and E. coli was 7 and 5 log units, respectively. Scalding, LA spray and air chilling all reduced (P < 0.05) the numbers of indicator bacteria on carcasses. Of the 55 samples each collected from BLA, ALA, ALA1, ALA2, and ACH, 36, 13, 2, 1 and 0 were positive for E. coli, respectively. In conclusion, pork processing environments can be contaminated with STEC from hides, feces and holding pen, but levels of STEC O157 appear to be low. Scalding, LA spray and air chilling can be effective measures to reduce the risk of bacterial contamination of pork.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.144

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 head0.005
GPT teacher head0.246
Teacher spread0.240 · 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