Features of Conclusion of Electronic Transactions Requiring a Notarial Certificate
Bibliographic record
Abstract
The urgency and urgent necessity to develop a research topic are due to a number of factors. First of all, the legal community unanimously reached a consensus on the necessity to reform the institution of notaries in the direction of expanding the powers and functions of public and private notaries, increasing the requirements for these participants in the context of the procedure of certification of transactions (contracts) in various fields. The reform of the Ukrainian notary has recently exhausted its potential and positive expectations on the part of civil society, which is only complicated by the progressive situation with the spread of acute respiratory infections caused by the COVID-19 SARS-CoV-2 virus. The purpose of this article was to objectively outline the existing problems in the field of law enforcement, related to the peculiarities of electronic transactions that require notarization, with the formulation of author's proposals to improve legislation in this area. The study was conducted using a number of general and special methods, a key role among which was played by comparative legal and statistical-prognostic methods, which were used to thoroughly analyze the current state of affairs in the field of electronic certification of transactions by notaries. As a result of the study, the authors concluded that in the development of the global information society and digital economy, the issue of electronic transactions requiring notarization needs further involvement of both theoretical and scientific research, as well as the development of practical solutions and proposals to improve the electronic interaction system.
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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 | 0.001 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".