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The evaluation of cryptocurrency

2019· article· en· W2964082811 on OpenAlexaboutno aff
Александра Шмырева, Pavel P. Baranov, Сергей Самохвалов, Sergey Samohvalov

Bibliographic record

VenueAuditor · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsCryptocurrencyLegislatureBusinessValue (mathematics)Money launderingGoods and servicesEconomicsCommerceComputer scienceComputer securityFinanceEconomyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The article estimate some aspects of the functioning of cryptocurrency, as a relatively new financial market instrument, the main participants in this market segment, cryptocurrency exchanges, taking into account key criteria: accessibility, mobility, operational efficiency. The aspects of regulation at the world and national levels are investigated.
 The authors give an assessment of the mechanism for regulating cryptocurrencies in separate countries ,which recognize this instrument and actively regulate it (Ar-gentina, Canada, Japan, Malazia, Switzerland),as well as countries, which reject (Vi-etnam) or just tolerate cryptocurrency, but do not have the regulatory framework for it use.
 Obviously, cryptocurrency is a relatively new instrument of the financial market, but its value not depend with amount of labour invested, as it is traditionally charac-teristic for conventional goods and services.
 The research shows that bitcoin still remains the most widespread type between other different kinds of cryptocurrencies.
 A significant aspect of cryptocurrencies functioning is their regulation. In our country there is no legislative certainty yet, but some steps have been made in this di-rection.
 In the long term, cryptocurrencies will be regulated at the international level, and the emphasis will be on preventing the use of their illegal financial transactions and for money laundering.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.005

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 head0.048
GPT teacher head0.271
Teacher spread0.222 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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