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Record W7057120588

Improving shelf-life of bison steaks treated with oregano and rosemary extracts

2018· dissertation· en· W7057120588 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPalatabilityMetmyoglobinLipid oxidationShelf lifePositive control
DOInot available

Abstract

fetched live from OpenAlex

The effects of plant extracts (non-enhanced, 0.05 % rosemary and 0.08% oregano extracts in the final product at a 10% pump level) on shelf life traits and consumer acceptability of bison striploin steaks were studied. Oregano steaks presented lower oxygen consumption and higher metmyoglobin reducing activity (MRA), decreased lipid oxidation and provided a stable red colour with less discolouration during the retail display period than the control and rosemary steaks (P < 0.05). Consumers indicated that treated steaks under study were not significantly different to the control group (P > 0.05) on palatability attributes and acceptability. However, rosemary injected steaks were more desirable and palatable than oregano counterpart (P < 0.05). In conclusion, plant extracts, particularly oregano, can considerably improve colour stability of bison steaks due to its antioxidants properties and ability to increase MRA capacity in the bison meat without posing any negative impact on its sensory attributes.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 head0.009
GPT teacher head0.207
Teacher spread0.197 · 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 designObservational
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

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