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QUALITY ESTIMATION OF HATCHING EGGS OF THE CZECH DOMINANT CROSS AND THE RESULTS OF YOUNG CHICKEN REARING IN CASE OF APPLICATION OF A PROBIOTIC ADDITIVE IN THEIR RATION

2021· article· en· W4211246031 on OpenAlexaff
V. I. Kotarev, Л. И. Денисенко, V.V. Shipilov

Bibliographic record

VenueVestnik of Ulyanovsk state agricultural academy · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsHatchingBiologyYolkEggshellAnimal scienceFlockHatcheryFood scienceEcologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The results of physical, morphological, biochemical studies of hatching eggs of hens of the parent flock of the Czech Dominant cross are presented. The study was carried out in the conditions of the poultry farm of Krasnoye Podvorie farm in Belgorod region. For further analysis of the results of egg hatching and subsequent analysis of growth and development of the resulting chickens, a scientific experiment was carried out on the first seven days of growth and development. The experimental group of chickens received a probiotic feed additive starting from the first hours of life to normalize the microflora of the gastrointestinal tract, to increase survivability and productivity of farm animals. The additive contains Bacillus megaterium B-4801, Enterococcus faecium 1-35, in the amount of 0.5 kg per 1000 kg. The control group received only balanced feed of the ration . Evaluation of hatching eggs of the Czech Dominant cross at 72-week reproduction period showed that all morphological parameters of the eggs corresponded to appropriate values: egg weight - 61.94 g, shell weight - 7.09 g, shell thickness - 0.352 mm, egg density - 1.080 g / cm3. The concentration of vitamins and acid number of the yolk of hatching eggs also does not exceed the norms for hatching chicken eggs: vitamin A - 8.7, carotenoids - 15.0 μg / g, vitamin B2 - 9.6 μg / g, acid number of yolk - 4.05 mg KOH / g.

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)0.000
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 score0.637
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.276
Teacher spread0.257 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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