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State information system “AITS”: features of formation and directions of development

2021· article· en· W4242464780 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the National Academy of Sciences of Belarus Agrarian Series · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsLivestockIdentification (biology)AgricultureEuropean unionBusinessAnimal husbandryRanking (information retrieval)Food securityGeographyInternational tradeComputer scienceForestryEcology

Abstract

fetched live from OpenAlex

Animal breeding is a strategic branch of agri-business in the Republic of Belarus, focused on solving social and economic issues and ensuring national food security. Currently, its development is innovations based, forming a high level of the country’s production and export potential. In the world ranking by the end of 2020, the Republic of Belarus took the 5th place in terms of milk exports (4.8 million tons). As world experience shows, the key direction is implementation of electronic identification of animals as an accounting system in agriculture, including assigning identification number to an animal by tagging, registering information about it in a database and issuing an appropriate passport. The paper summarizes and systematizes legal, organizational and financial conditions for creation and functioning of national information systems in Australia, Argentina, Brazil, Great Britain, the European Union, Canada, the Netherlands, the USA, Switzerland, and Japan. It has been determined that absence of a system for identifying the registration of farm animals leads to distortion of data on the number of livestock, and also creates obstacles for selection work and livestock breeding, decreases efficiency of antiepizootic measures, and inhibits international trade in animals and animal products. In development of this, the necessity of this process in the Republic of Belarus, feasibility of creating the state information system “AITS” (SIS AITS) and corresponding management structure – SI “Center for information systems in animal husbandry” are substantiated. With Gomel region as an example, peculiarities of planning and implementation of process of identification and registration of farm animals are disclosed, the main indicators of the efficiency of SIS AITS for 2013–2020 are analyzed. The advantages of commodity producers of the Republic of Belarus in the context of strengthening production and marketing and export potential and reducing risks in the domestic and foreign markets are substantiated. The issues presented in the article are of interest in determining measures for implementation of the State Program “Agrarian Business” for 2021-2025 and a strategy for the export of agricultural products and food products for the period up to 2025.

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.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.016
GPT teacher head0.203
Teacher spread0.187 · 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