The evaluation of cryptocurrency
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".