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Record W2110187042 · doi:10.1109/08ias.2008.89

Survivability of Inoculated Versus Naturally Grown Bacteria in Liquid Foods under Pulsed Electric Fields

2008· article· en· W2110187042 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of GuelphUniversity of Waterloo
Fundersnot available
KeywordsPasteurizationInoculationBacteriaEscherichia coliFood scienceElectric fieldChemistryMicrobiologyBiologyHorticultureBiochemistry

Abstract

fetched live from OpenAlex

In this paper, the effect of different pulse and system parameters on the killing efficiency of PEF treatment was investigated. Escherichia Coli bacteria inoculated in apple juice was treated. The results showed that an electric field higher than 4 kV/mm is required to enhance the killing efficiency using PEF that has sufficient log reductions in the microbial numbers. The temperature rise during pulse application was found to be around 20degC, and it is observed that this rise in medium temperature has synergistic effect and has resulted in high inactivation. As the temperature rise can be limited to a value below the pasteurization temperature, the synergistic effect can be highly beneficial. While high killing rate was achieved for inoculated bacteria (3-4 log reduction), less than 2 log reduction was achieved for naturally growing bacteria in apple juice under the test conditions used.

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 score0.027
Threshold uncertainty score0.464

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 head0.030
GPT teacher head0.294
Teacher spread0.265 · 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

Quick stats

Citations4
Published2008
Admission routes1
Has abstractyes

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