Unique Regulatory Approach for Licensing the Port Hope Remediation Project in Canada - 13315
Bibliographic record
Abstract
The Port Hope remediation project is a part of a larger initiative of the Canadian Federal Government the Port Hope Area Initiative (PHAI) which is based upon a community proposal. The Government of Canada, through Natural Resources Canada (NRCan) is investing $1.28 billion over 10 years to clean up historic low-level radioactive waste in the Port Hope Area and to provide long-term safe management of the low-level radioactive wastes in the Port Hope Area. These wastes arose from the activities of a former Federal Crown Corporation (Eldorado Nuclear) and its private sector predecessors. In Canada, historic waste are defined as low-level radioactive waste that was managed in a manner no longer considered acceptable, but for which the original producer cannot reasonably be held responsible or no longer exists and for which the Federal Government has accepted responsibility. In Canada, under the current regulatory framework, the environmental remediation is not considered as a distinct phase of the nuclear cycle. The regulatory approach for dealing with existing sites contaminated with radioactive residues is defined on the basis of risk and application of existing regulations. A unique regulatory approach was taken by the Canadian Nuclear Safety Commission (CNSC) to address the various licensingmore » issues and to set out the requirements for licensing of the Port Hope Project within the current regulatory framework. (authors)« less
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".