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Record W4402496522 · doi:10.24874/pes06.03a.014

INFORMATION SYSTEMS MANAGEMENT IN AGRITECH FOR FOOD SECURITY

2024· article· en· W4402496522 on OpenAlexaboutno aff
Olim K. Abdurakhmanov, Andrey V. Kuklin, Abdumalik M. Kadirov

Bibliographic record

VenueProceedings on Engineering Sciences · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsnot available
Fundersnot available
KeywordsFood securityBusinessInformation security managementInformation securityComputer scienceSecurity information and event managementComputer securityCloud computing securityAgricultureBiologyEcologyCloud computing

Abstract

fetched live from OpenAlex

In this paper, we considered and characterised the features of information systems management of agricultural production processes, which are based on agricultural technologies to support and increase food security in the domestic and external markets.We revealed management models in this category, which are used in the agrarian sector of Canada and Vietnam.Differences between these two models are connected with several factors, including socioeconomic development, quality of arable land, availability of resources and their cost, level of labour resources' readiness to the implementation of new ICT, and farms' adopting the necessity of transition to precise farming.The revealed advantages and problems of implementing Agritech at the level of the two countries demonstrate that the focus on sustainable and precise farming has become a new trend in this sphere.The goal of this paper was to establish the features of the formation of approaches to information systems management in Agritech to ensure the food security of countries that produce agricultural products.The scientific novelty of this paper lies in the determination of approaches to the implementation and management of information systems in the considered category, which facilitate the creation of conditions for the growth of efficiency of agricultural productions under the influence of threats of climate change.

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 categoriesScholarly communication
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 score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.032
GPT teacher head0.254
Teacher spread0.223 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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