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Record W2801566050 · doi:10.15421/nvlvet8432

Adaptive ability of the poultry and its importance in the selection of animals

2018· article· en· W2801566050 on OpenAlexaboutno aff
H. A. Paskevych, A. V. Hunchak, L. M. Fialovych

Bibliographic record

VenueScientific Messenger of LNU of Veterinary Medicine and Biotechnology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProductivitySelection (genetic algorithm)BiologyProduction (economics)Adaptation (eye)PopulationAgricultureAgricultural scienceBiotechnologyCommodityInheritance (genetic algorithm)BusinessEcologyEconomicsEconomic growthGeneticsMicroeconomicsDemographyComputer science

Abstract

fetched live from OpenAlex

An important property of living organisms is the ability to adapt to the influence ofthe externalfactors that is constant adaptation to environmental changes, while preserving the constancy of the internal environment. At the present levelof thedevelopment of poultry farming in agro farms of different types, the choice of the most adaptive and competitive breeds and crossbreds of the poultry in the production of eggs and meat is of great importance. Farm animals are affected by various external factors such as technology of keeping, production, veterinary and prophylactic and zootechnical measures. According to various scientific sources, a significant number of poultry crosses are used in Ukraine, mainly for the selection of leading firms in the USA, Canada, and Western Europe (foreign breeds in Ukraine account about 80% of the total poultry population). They provide a high degree of implementation of the genetic productivity potential, butunder rather controlled, almost climatic conditions of keeping and feeding. At the same time, they are very responsive to changing of environment when used in the conditions of the breeding and commodity enterprises of Ukraine. This is due to the fact that the main economic-useful signs of the bird (bearing, weight of eggs, reproductive qualities) have polygenic inheritance and, accordingly, have a small fate of additivity of the operating genes. Therefore, in the new conditions of exploitation of cross-breeds of foreign selection on the indicated signs there is a significant influence of interaction «genotype × environment», which reduces the combinational ability of the family farms and, accordingly, manifestation of the heterosys effect. To preserve the structure of the cross, adaptation of the original family forms to the specific conditions of the poultry holdings is necessary, and then the implementation of supporting selection during mass selection of repair young animals. It should be taken into account that the suitability of imported lines, family forms or final bird hybrids is limited to the limits of their physiological response, since their heredity is formed in the conditions of the country where they are bred. The problem of adaptation of poultry in the conditions of industrial poultry farming is constantly relevant. The intensification of the industry leads to the new adaptation factors, in particular, different technological conditions for repair young animals and adult herds, changes in the recipes of feed and the quality of their components in other regions, the movement of poultry, stresses and so on. At the present, it is important to take into account both adaptive responses, acclimatization capacity of poultry and other animals imported from abroad, and selection according to the indicators of the reaction of the body for different methods of their study. In this regard, it is advisable to use crosses that have high adaptive capabilities.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.278
Teacher spread0.217 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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