Elevated radioactive contamination from the Fukushima nuclear power plant accident in aquatic biota from a river with a lake in its upper reaches
Bibliographic record
Abstract
Five years have passed since the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident occurred. Forests, streams, and lakes remain radioactively contaminated, with slight sign of convergence. The radiocesium concentration of brown trout (Salmo trutta) in Lake Chuzenji (160 km from the FDNPP) still exceeds the Japanese regulatory limit of 100 Bq·kg−1, likely due to elevated contamination in Lake Chuzenji. In this study, the concentration of 134Cs and 137Cs in algae, litter, sand substrate, and aquatic insects in a river originating from Lake Chuzenji (Daiya site) and in a nearby river (Watarase site) from 2013 to 2015 were compared. At the Daiya site, 134Cs and 137Cs concentrations of algae and aquatic insects were high (e.g., 137Cs in algae: 160 Bq·kg−1 at the Watarase site and 320 Bq·kg−1 at the Daiya site) and still increasing in some groups such as Perlodidae and Heptageniidae, though the mean air dose rate (0.05 μSv·h−1) was lower than that at the Watarase site (0.11 μSv·h−1). We attributed this to high flow out of higher 134Cs and 137Cs concentration originating from Lake Chuzenji. Thus, lower reaches fed by contaminated headwaters will likely experience prolonged contamination.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".