Dosimetric analysis of fathead minnow (<i>Pimephales promelas</i>, Rafinesque, 1820) exposed via ingestion to environmentally relevant activities of Ra-226 for two years
Bibliographic record
Abstract
PURPOSE: To assess the dosimetry of Ra-226 in a two-year chronic ingestion study in laboratory maintained fathead minnow fed environmentally relevant levels of the isotope known to occur in gut contents of fish from a uranium mining area. METHODS: Fish were established on reconstituted commercial fish food containing 10 mBq-10 Bq Ra-226.g(- 1) dry food. The fish were sampled at 1, 6, 18 and 24 months and the Ra-226 levels in the whole fish were directly determined using measurement performed using inorganic mass spectrometry. Pilot experiments using higher doses were also done during development of a liquid scintillation detection system which support some data. RESULTS: The data show that after 1 month the levels of accumulation in the fish were below detection. At 6 months there was an activity dependent accumulation which was relatively higher in the low activity groups. By 18 and 24 months the radium was very low in all groups - well below 6 month levels suggesting considerable loss of radium from the fish. These data were confirmed in a small and shorter study using higher dietary activities. The highest dose calculated for any measurement point was 16 μGy.h(- 1) in the 6-month-old fish fed the diet containing 10 Bq.g(- 1). CONCLUSIONS: We conclude that environmentally relevant levels of Ra-226 have a maximum impact at early time-points when the fish are still growing. After that they appear to depurate accumulated radium. In terms of environmental impact, the maximum accumulation peaks at the age where fish could be spawning but is extremely low leading to μGy.year(- 1) doses even after exposure to the high activity diets.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".