Comparison of transfer parameters in TRS-472 and Canadian standard CSA N288.1 and doses predicted using them
Bibliographic record
Abstract
We compared parameter values and models in N288.1 and TRS-472 and the doses predicted using them. The parameter values and models for tritium and C-14 are similar. For other radionuclides, the parameter values agree well for soil to plant transfer, and forage to animal products transfer. Agreement is not always good for the translocation factor (for which N288.1 is often more conservative) and for soil and sediment Kd and freshwater fish BAFs (for which N288.1 is often less conservative). Using parameter values from N288.1 rather than using those from TRS-472 results in higher doses for 8 of 9 radionuclides for airborne releases, and for 5 of 9 radionuclides for aquatic releases. For airborne releases, the maximum difference occurs for I-131, where using N288.1 parameter values results in doses being seven times higher. For aquatic releases, the difference reaches a factor of 194 for Co-60, with the use of N288.1 parameter values resulting in the lower dose. Where differences exist, site-specific values for key radionuclides should be obtained through a review of available data or new experiments. In the absence of site-specific data, the more conservative of the values in N288.1 and TRS-472 should be used.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".