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Record W102029170

Результаты использования импортных мясных пород свиней при скрещивании в Сибири

2012· article· ru· W102029170 on OpenAlexaboutno aff
В. А. Бекенёв, В. И. Фролова, И.В. Боцан, Ю. В. Фролова, М.И. Харсеева, А. А. Заболотная, С.И. Гаптар, A. N. Golovko

Bibliographic record

VenueAchievements of Science and Technology in Agro-Industrial Complex · 2012
Typearticle
Languageru
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPurebredCrossbreedBreedLarge whiteAnimal scienceBiologyAnimal breedingVeterinary medicineMedicine
DOInot available

Abstract

fetched live from OpenAlex

A study the effectiveness of crossing sows of Large White breed with Yorkshire boars the Canadian breeding and Landras boars Irish breeding of various combinations. The average daily gain of crossbred (Large White x Yorkshire) were fattening up 751g, against 728 g in control, that is was higher in 23 grams. The thickness of the fat they reached 26.5 mm or 24.5% less than in the controls. In hybrid (Large White x Yorkshire) x Landrace daily gain was higher in the 61g compared with the control group, fat thickness was 23.6 mm. As a result of tasting the meat was better than purebred animals from Novosibirsk type of large white breed and hybrid (Large White x Yorkshire) x Landrace. Fat three-breed cross, where the breed was the final selection of Irish landraces, has a lower melting point

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0010.006
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.111
GPT teacher head0.306
Teacher spread0.196 · 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.

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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueAchievements of Science and Technology in Agro-Industrial ComplexSame topicAnimal Nutrition and HealthFrench-language works237,207