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Record W2177836403 · doi:10.5539/mas.v9n10p45

The Effect of Different Body Conformation Types on Beef Quality in Young Bulls

2015· article· en· W2177836403 on OpenAlexvenueno aff
Kinispay М Dzhulamanov, М. П. Дубовскова, Nikolay P Gerasimov, Gulzhan N. Urynbaeva

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
Fundersnot available
KeywordsDry matterNutrientAnimal scienceComposition (language)BiologyFood scienceAdipose tissueMoistureChemistryBiochemistryEcology

Abstract

fetched live from OpenAlex

The chemical composition analysis of average meat samples and M. longissimus dorsi testify that the greatest nutrients variability characterizes fat, the protein and mineral substances of carcasses edible part possess relative stability. In the study of qualitative structure of slaughter products the general regularity was revealed – increase of dry matter and fat contents and decrease in moisture with age. The process of fat deposition in the pulp of carcasses of compact body type genotypes was more intensive. That led to the maximum size (38,04%) of dry matter contents. Intensive accumulation of adipose tissue in compact body conformation group of bull-calves already had began with one-year-old age and to 15-month age the protein and fat ratio reached 1:0,65. At the age of 21 months tall animals were the best protein and fat ratio: they had ratio 1:0.83 instead 1:1.28 and 1:0.99 at compact and the medium contemporaries. Compact bull-calves had the highest of a forage’s protein and energy expenses into own body nutrients, the smallest had tall contemporaries.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.039
GPT teacher head0.281
Teacher spread0.242 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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