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Record W2896783945 · doi:10.1139/cjas-2018-0090

The effect of age and ultimate pH value on selected quality traits of meat from wild boar

2018· article· en· W2896783945 on OpenAlexvenueno aff
Marek Stanisz, Agnieszka Ludwiczak, Joanna Składanowska‐Baryza, Marta Bykowska

Bibliographic record

VenueCanadian Journal of Animal Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
Fundersnot available
KeywordsBOARBiologyAnimal scienceLightnessFood scienceWild boarChemistryEcologyBotany

Abstract

fetched live from OpenAlex

The meat from hunted wild boar juveniles (N = 18) and yearlings (N = 17) was analysed to assess the influence of age and the ultimate pH value on selected quality traits. The analysed meat of 55.56% of the juveniles and 64.71% of the yearlings was characterised with normal pH. The pH had been measured 24 and 48 h post mortem. More cases of high ultimate pH (pH u > 5.8) and high maximal pH (about 6.2) have been noted in the meat of younger animals compared with older ones. We found no effect of pH u on the colour coordinates of analysed wild boar meat. A slight effect of age was observed for the lightness (L*) coordinate. The postmortem time was the most important factor influencing meat colour [L*, yellowness (b*), and hue angle]. A high pH u was related to lower drip loss (P = 0.001), lower percentage of free water (P = 0.036), lower cooking loss (P = 0.001), and lower plasticity (P = 0.042). The meat from juveniles showed higher plasticity than meat from yearlings. Summing up, both the pH u level and the age of wild boars may affect some qualitative patterns of meat, changing the technological usability of this raw animal product.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.031
GPT teacher head0.268
Teacher spread0.236 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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