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Record W2727470892

PRODUCTION OF POULTRY MEAT AND EGGS IN THE REPUBLIC OF CROATIA AND IN THE EUROPEAN UNION

2017· article· en· W2727470892 on OpenAlexaff
Igor Kralik, Zrinka Tolušić, Davor Bošnjaković

Bibliographic record

VenueUniversity of Zagreb University Computing Centre (SRCE) · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsLivestockPoultry meatPer capitaProduction (economics)European unionConsumption (sociology)Agricultural sciencePoultry farmingAgricultural economicsBusinessGeographyBiologyFood sciencePopulationInternational tradeEconomics
DOInot available

Abstract

fetched live from OpenAlex

Poultry meat and eggs are a significant source of nutrients in the human diet. Poultry products are widely consumed because they are nutritionally valuable, there are no religious restrictions on consumption, it is relatively easy to prepare diverse meals based on poultry, and the price of such products is relatively low. The aim of this research was to investigate the development of poultry production in the Republic of Croatia in the period 2010-2014, comprising the period of two years after Croatia joined the EU. The paper also compares data of poultry production in Croatia and in the EU. Over the period in question, total meat production in Croatia was reduced by 23%, meat import was increased by 45%, poultry meat export was increased by 46%, and production of eggs decreased by 20%. At the same time, in the EU countries poultry production was increased by 8.8% on average, export was increased by 10%, and import was reduced by 3.7%, while the egg production stagnated. In 2014, consumption of poultry meat in Croatia was 18.3 kg per capita, and in the EU 26.8 kg per capita. Self-sufficiency in the poultry production over the analyzed period was not satisfactory, therefore in the coming years, Croatia will have to develop quickly this important branch of livestock breeding. In addition to conventional production, faster development refers to production of organic and functional poultry products. Keywords: Poultry meat production, egg production, consumption, Croatia, EU

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)0.001
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.012
GPT teacher head0.181
Teacher spread0.169 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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