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Record W2513536914

Качество и технологические свойства мяса свиней канадской селекции

2014· article· ru· W2513536914 on OpenAlexaboutno aff
С.А. Грикшас, Г. А. Фуников, М Р Аббасов, Н С Губанова

Bibliographic record

VenueAgrarian Bulletin of the · 2014
Typearticle
Languageru
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCrossbreedPurebredBreedBiologyVeterinary medicineAnimal scienceCarcass weightBody weightMedicine
DOInot available

Abstract

fetched live from OpenAlex

The article provides the results of studies of morphological composition of carcasses, physical-chemical characteristics and a tasting estimation of the pork of Canadian selection. The experiment was conducted at the pig farm Troparyovo in the period of 2011-2013. The object of the research were purebred and crossbred animals, carcasses and half-carcasses, muscle tissue and boiled meat of the Canadian selection pigs. Pigs for the experiment were selected on the basis of peers in age, body weight and breed, according to the scheme of studies. The object of the research were Canadian selection pigs: 1 pure-bred Yorkshire pig breed, 2 hybrid animals (Landrace x Yorkshire), 3 three-breed (Yorkshire x Landrace x Duroc), 4 crossbred animals (Yorkshire χ Landrace χ terminal boar). Morphological composition of carcasses showed that the highest yield of a muscle tissue was obtained from carcasses of young crossbred (Landrace x Yorkshire x terminal boar) 64.8 %. The muscle tissue yield of crossbred youngsters in this group was more for 7.8 % (P pork from three-pedigree youngsters produced using Duroc boars has a better tasting estimate. It is recommended to use pigs of the Canadian selection to increase a productivity and quality of meat.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.168
Teacher spread0.157 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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