LEGAL REGULATION OF GENETIC RESEARCHES IN THE RUSSIAN LEGISLATION IN THE CONTEXT OF THE PROBLEM OF GENDER VERIFICATION IN SPORT
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.
Bibliographic record
Abstract
Modern achievements of geneticists, which have made it possible to map the genes of inherited diseases, have set the legislator a rather difficult task to determine the grounds and limits of the use of relevant information in various spheres of public life, including insurance. At the same time, in some countries, the emphasis is on legislative regulation, which in the case of a Federal structure of the state can be carried out at different levels (USA, Canada), in others, more importance is attached to self-regulation (great Britain, Australia). The range of issues covered by the regulation is very diverse in both cases and may include: assessment of the possibility of referral for genetic research, which is usually excluded, access to existing results of genetic research, which may be restricted by a ban on their use; the right to collect genetic information without conducting genetic testing, which is recognized by the actual practice of analyzing family history; determining the conditions and limits for the use of genetic information, which are usually associated with obtaining the consent of the policyholder, ensuring the confidentiality of personal data and only for the purposes for which it was collected; establishing a correlation between the exercise of the right to access genetic data and the amount of insurance coverage, which may decrease if favorable data is obtained that contradicts the conclusions made on the basis of family history
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it