Environmental radionuclide concentrations below which non-human biota experience no effects
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
Conservative no-effect concentrations were derived for nine radionuclides, four generic organisms (terrestrial plant and animal and aquatic plant and animal) and six environmental compartments (air, soil, fresh water, marine water, freshwater sediments and marine sediments). The concentrations were calculated using the concentration ratio (CR) approach that is used in both FASSET and RESRAD-BIOTA. In the CR approach, a single transfer factor is used to predict concentrations in plants or animals from concentrations in soil or water. Most of the CR values required for the calculations were taken from FASSET documentation. Because of the importance of tritium and C-14 in the context of CANDU reactors, CR values for these radionuclides were derived from specific activity (SA) concepts. Sediment partition coefficient (Kd) values, which were used to derive no-effect levels for sediments from the levels for water, were chosen to be the best-estimate values from the IMPACT database. Dose conversion coefficients (DCCs) were taken from FASSET and the dose rate benchmarks used were those recommended by UNSCEAR. The results provide environmental concentrations below which no detrimental effects are expected on non-human biota at CANDU sites in Canada.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it