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Record W3120395200 · doi:10.1051/shsconf/20219304012

E-commerce Trends and Opportunities in BRICS countries

2021· article· en· W3120395200 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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 score0.897
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.054
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