Toward a modification of the soil compartment of the CSA N288.1 environmental transfer model for permafrost conditions
Bibliographic record
Abstract
The Canadian road map for Small Modular Reactors (SMRs) details that possible uses for SMRs includes providing electricity to remote communities. Many of the communities in the Canadian Arctic use diesel fuel generators to provide electricity. SMRs provide a possible future alternative to the combustion of fossil fuels in these communities. This has been done before by the United States Army Nuclear Power Program (ANPP) and Russia currently uses two SMRs to supply electricity in the Arctic. For power reactors in Canada, Derived Release Limits must be calculated using the N288.1 environmental compartment model. There is a compartment for soil in the N288.1 model that includes a few different soil types. However, the compartment is not suitable for soils that are underlain by permafrost (cryosols). In this paper we describe how the N288.1 soil compartment could be modified for permafrost conditions, and specifically those representative of the continuous permafrost zone, where 90–100 % of the ground underlying the surface is perennially frozen. We provide example calculations using the modified version of the N288.1 soil compartment representative of conditions around Inuvik, a site in continuous permafrost. In general the specific calculations of the modified N288.1 standard tend to decrease the value of the P 13 (air to soil) transfer factor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".