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Record W2324078492 · doi:10.1139/cjas-2015-0001

Effects of electrical stimulation on meat quality of bison striploin steaks and ground patties

2016· article· en· W2324078492 on OpenAlexafffundvenue
C. Ding, Argenis Rodas‐González, Ó. López-Campos, J. K. Galbraith, M. Juárez, I. L. Larsen, Ye Jin, J.L. Aalhus

Bibliographic record

VenueCanadian Journal of Animal Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsAgriculture Food and Rural DevelopmentAlberta Livestock and Meat AgencyAgriculture and Agri-Food Canada
FundersChina Scholarship CouncilAgriculture and Agri-Food CanadaAlberta Livestock and Meat Agency
KeywordsMarbled meatLean meatAnimal scienceBiologyStimulationFood scienceEndocrinology

Abstract

fetched live from OpenAlex

As bison is characteristically dark in colour, this study was conducted to determine if high-voltage electrical stimulation (HVES) could improve the colour and other quality characteristics in bison, similar to positive effects of HVES previously observed in beef. Forty bison bull carcasses were split and HVES (400 V peak, 5 ms pulses at 15 pulses s−1 for 30 s) was applied to the right sides and subsequently evaluated for grade characteristics, metabolic activity, and quality characteristics. The bison carcasses used in this study had a wide range of lean and fat, with minimal marbling. In the present study, HVES had no effect on bison quality traits, sensory attributes, retail display characteristics, nor the glycolytic metabolites (P > 0.05) except lactate. Inherent differences in muscle fibre type or physical carcass differences may have influenced the response to the electrical parameters used in the present study and merits further investigation.

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 score0.005

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 head0.048
GPT teacher head0.273
Teacher spread0.225 · 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

Citations5
Published2016
Admission routes3
Has abstractyes

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