Impact of the 2019 typhoons on sediment source contributions and radiocesium concentrations in rivers draining the Fukushima radioactive plume, Japan
Bibliographic record
Abstract
The Fukushima nuclear accident in March 2011 generated a 3000 km 2 plume of soils heavily contaminated with 137 Cs. Decontamination was completed early in 2019. Typhoon Hagibis was the first extreme event that occurred in the region after decontamination. Its impact on sediment sources and sediment 137 Cs contamination was investigated through the application of a sediment fingerprinting procedure using spectrocolorimetry and geochemical properties. Sediment deposits ( n = 24 ) were collected in the Mano and Niida River catchments after the 2019 typhoons, and their signature was compared to that of potential sources (e.g., cropland, forests, and subsurface; n = 57 ). Results demonstrate the dominance of cropland as the main source of sediment (mean: 54%) followed by forests (41%) with much lower contributions of subsurface material (5%). Overall, 137 Cs concentrations in sediment were on average 84%–93% lower than the levels recorded after the accident in 2011, which demonstrates the effectiveness of cropland decontamination.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".