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Improved use of oxygen scavengers to stabilize the colour of retail-ready meat cuts stored in modified atmospheres

2002· article· en· W2063720467 on OpenAlexafffund
Gaurav Tewari, L.E. Jeremiah, Digvir S. Jayas, Richard A. Holley

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsModified atmosphereTrayOxygenAtmosphere (unit)ChemistryAbsorption (acoustics)Materials scienceFood scienceComposite materialShelf lifeMechanical engineeringEngineeringOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract A series of three experiments were conducted to develop a retail packaging system suitable for use in centralized meat processing and packaging operations using modified atmosphere master packaging (MAP) of display-ready beef and pork cuts. It was shown that oxygen (O2) scavengers were needed inside retail trays, lidded or over-wrapped trays could be used with equal success but inclusion of a grid inside the retail tray was not required. It was established that a minimum of eight O2 scavengers with an O2 absorption rate high enough to achieve an O2 half-life of 0.6–0.7 h in the pack atmosphere were needed where the O2 concentration could otherwise remain ≤500 ppm at any time during storage. Composite results from these experiments clearly showed that the best performance resulted from use of hard plastic retail trays containing eight O2 scavengers, with high O2 absorption rate, when placed underneath an absorbent pad and over-wrapped with an O2 permeable film. Small holes in two corners of the O2 permeable film to permit free exchange of atmospheres within the retail packages facilitated O2 reduction during MAP storage.

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)0.001
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 score0.121
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.275
Teacher spread0.194 · 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

Citations32
Published2002
Admission routes2
Has abstractyes

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