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RADIO‐FREQUENCY HEATING OF HAM TO ENHANCE SHELF‐LIFE IN VACUUM PACKAGING

2004· article· en· W1565024356 on OpenAlexafffund
Valérie Orsat, Li Bai, Vijaya Raghavan, James P. Smith

Bibliographic record

VenueJournal of Food Process Engineering · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMoistureShelf lifePasteurizationVacuum packingFood sciencePlastic packagingRadio frequencyMaterials scienceWater contentPlastic filmComposite materialChemistryTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Radio‐frequency heating at 27.12 MHz was studied for the pasteurization of ham samples repacked in plastic films. The samples were brought to internal temperatures of 75C and 85C in 5 min and maintained at those temperatures for an additional 5 min. The ham samples were vacuum‐packed in three different plastic films and stored at 4C for 1 to 28 days. All samples were examined for moisture loss, colour change, sensory quality attributes such as off odors and sliminess, and total bacterial surface counts. The study indicates that radio‐frequency heating, coupled with appropriate packaging, can improve the storability of repacked hams by reducing the bacterial load, reducing moisture loss and maintaining an overall greater product sensory quality and acceptance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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 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

Citations37
Published2004
Admission routes2
Has abstractyes

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