Analysis of regulatory and legal framework to ensure the realization of Canadian national biosafety and biosecurity program in the context of bioterrorism
Bibliographic record
Abstract
The article examines the regulatory and legal framework realization of Canadian National Biosafety and Biosecurity Program in the context of bioterrorism. Based on an analysis of Canadian law, it is shown that the creation of a regulatory system for this program is divided into several stages from the development of a general strategy to the creation and entry into force of specific legal acts that regulate in detail the order of research, storage and use of biologically dangerous agents and their toxins. At present, activities in the field of biomedical research in Canada are conducted according to national standards, and monitoring of their implementation in order to counter threats to biological nature provided by specially created state agency that is responsible for the administration and implementation of legislated Biosafety and Biosecurity Program. It is suggested to use the positive experience of Canada in Ukraine to create an appropriate national security system for countering bioterrorism, biological sabotage and other biological threats. Key Words: bioterrorism, biothreats, bio-risks, biological security, biological protection.
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 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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".