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Record W3120395200 · doi:10.1051/shsconf/20219304012

E-commerce Trends and Opportunities in BRICS countries

2021· article· en· W3120395200 on OpenAlexaff
Svetlana Gusarova, Igor Gusarov, Margarita Smeretchinskiy

Bibliographic record

VenueSHS Web of Conferences · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsYork University
FundersРоссийский экономический университет имени Г.В. Плеханова
KeywordsChinaBusinessInternational tradePlan (archaeology)Coronavirus disease 2019 (COVID-19)PandemicEconomic growthDevelopment economicsPolitical scienceEconomicsGeography

Abstract

fetched live from OpenAlex

Introduction of information technologies, transfer to the digital economy and the development e-commerce are on the agenda all over the world today. BRICS countries (Brazil, Russia, China, South Africa) pay great attention to the development of e-commerce and plan to strengthen intra-group cooperation in this area. An increase of the e-commerce is a new paradigm of the development of international trade of the «five» countries. It can become their economic growth driver, especially during the crisis due to the coronavirus pandemic. This problem is important, but still insufficiently studied and not enough reflected in the economic researches. Authors revealed the advantages, problems and the main directions of the development of e-commerce in BRICS countries.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.054
GPT teacher head0.229
Teacher spread0.175 · 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 designNot applicable
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

Citations5
Published2021
Admission routes1
Has abstractyes

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