Comparing the Radioactive Contamination of Marsh Labrador Tea (Ledum Palustre L.) Over Different Periods Since Chernobyl Accident
Bibliographic record
Abstract
Radioactive contamination of the above-ground phytomass of marsh Labrador tea (Ledum palustre L.) in different periods after the Chernobyl accident was studied. Marsh Labrador tea is widely used in official and folk medicine. The studied species grows in over-moistened pine (less mixed) forests and open oligotrophic and mesotrophic marshes. It was found that in the first four years since the beginning of observations (1991), the magnitude of the specific activity of 137Cs in above-ground vegetative phytomass of marsh Labrador tea, depending on a permanent sample area (PSA), decreased by 1.2–1.4 times. After 10 years, it decreased by 1.6–1.7 times, after 16 years by 1.9–2.1 times, after 21 years by 2.7–3.1 times, and after 27 years by 3.1–6.5 times. An increase in the magnitude of transitions factors was also observed on all PSA over time. Thus, the minimal increase within 1991–2018 was recorded in PSA 11 – by 1.2 times and on PSA 13 – by 1.4 times. The maximum decrease in the magnitude of transition coefficient was observed in PSA 16 – by 2.7 times, in PSA 15 – by 3.0 times, and in PSA 18 – by 2.0 times. It was found that marsh Labrador tea belongs to the group of plants that are characterized by the high content of 137Cs in the above-ground vegetative phytomass. Within the observation period (1991–2018), this content significantly exceeds the admissible levels of radionuclide content in plant medicinal raw materials that are used for manufacturing medical preparations. In the PSA with maximum magnitudes of soil contamination density (400.5±50.73 kBk·m-2) this excess made up 158.4 times in 1991, and 33.7 times (166.9±23.56 kBk·m-2) in 2018. For 27 years of observations, there has been a decrease in the density of radioactive soil contamination by 2.1–2.7 times, which is due to radionuclide decomposition, its vertical migration in the soil, and towards the components of forest ecosystems.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".