Sediment-Water Distribution Coefficients of Stable Elements in Four Estuarine Areas in Japan
Bibliographic record
Abstract
Sediment-water distribution coefficients (Kds) were obtained in estuarine areas of four A-class rivers in Japan. The total concentrations of stable elements and naturally occurring radionuclide (i.e., Na, Mg, K, Ca, V, Mn, Fe, Co, Ni, Cu, Rb, Sr, Y, Mo, Cd, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Pb, and U) in the estuarine water at each sampling point and in the corresponding sediment sample were measured. Kds of most of the elements varied within one order of magnitude regarding their differences between minimum and maximum values of each element at all the stations. However, a wide variation of Kds of Mn, Fe, Co, Cu, Rb, and La was observed. In addition, geometric means (GMs) of observed Kds were compared with the recommended values in the IAEA Technical Report Series 422 (TRS-422). The results showed that GMs of Kds for most of the elements agreed well with the recommended values, but GMs of Kds for Mn, Fe, and Cd were more than 10 times lower than the recommended values. The obtained Kd values could be important to investigate the behavior, transport, and fate of artificial radionuclide and to assess the radiological doses in estuarine areas.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".