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Record W2092280820 · doi:10.1111/jam.12749

Impacts of sporulation temperature, exposure to compost matrix and temperature on survival of <i>Bacillus cereus</i> spores during livestock mortality composting

2015· article· en· W2092280820 on OpenAlexaff
Kim Stanford, Tim Reuter, Brandon H. Gilroyed, Tim A. McAllister

Bibliographic record

VenueJournal of Applied Microbiology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food CanadaAgriculture Food and Rural Development
Fundersnot available
KeywordsCompostLivestockAgricultureCereusSporeBacillus cereusGeographyLibrary scienceAgricultural scienceBiologyArchaeologyForestryAgronomyBotany

Abstract

fetched live from OpenAlex

AIMS: To investigate impact of sporulation and compost temperatures on feasibility of composting for disposal of carcasses contaminated with Bacillus anthracis. METHODS AND RESULTS: Two strains of B. cereus, 805 and 1391, were sporulated at either 20 or 37°C (Sporulation temperature, ST) and 7 Log10 CFU g(-1) spores added to autoclaved manure in nylon bags (pore size 50 μm) or in sealed vials. Vials and nylon bags were embedded into compost in either a sawdust or manure matrix each containing 16 bovine mortalities (average weight 617 ± 33 kg), retrieved from compost at intervals over 217 days and survival of B. cereus spores assessed. A ST of 20°C decreased spore survival by 1·4 log10 CFU g(-1) (P < 0·05) compared to a 37°C ST. Spore survival was strain dependent. Compost temperatures >55°C reduced spore survival (P < 0·05) and more frequently occurred in the sawdust matrix. CONCLUSIONS: Sporulation and compost temperatures were key factors influencing survival of B. cereus spores in mortality compost. SIGNIFICANCE AND IMPACT OF THE STUDY: Composting may be most appropriate for the disposal of carcasses infected with B. anthracis at ambient temperatures ≤20°C under thermophillic composting conditions (>55°C).

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)0.001
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 score0.057
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.269
Teacher spread0.255 · 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 designBench or experimental
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

Citations8
Published2015
Admission routes1
Has abstractyes

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