Cs-137 in Sand and Seawater Samples from Piraquara Beach, Brazil: Discharge site of effluents from the Angra dos Reis Nuclear Power Plants
Bibliographic record
Abstract
This study presents the Cs-137 radionuclide concentration and activity in sand profile and seawater samples from Piraquara Beach (PB) and from an adjacent small stretch of sand used as a beach. Both sites are located near the discharge point for cooling water and liquid effluents from the Almirante Álvaro Alberto Nuclear Power Station (CNAAA) in Brazil. The chemical composition of the sand samples was determined by granulometric analysis, elemental chemical characterization, and X-ray diffraction (XRD). Mineral sorbents for the Cs-137 radionuclide were found close to the discharge point. The presence of Cs-137 radionuclides in sand and seawater samples was determined by gamma spectrometry analysis, which was also used for seawater samples after absorption by ammonium phosphomolybdate (APM). The Cs-137 radionuclide activity measurements were lower than the minimum detectable activity (MDA): sand < 0.31 Bq.kg-1, direct analysis of seawater < 0.42 Bq.L-1, and seawater with APM < 0.004 Bq.L-1. The aim of this study was to measure the amount of the Cs-137 radionuclide in the deeper layers of PB. A determination of radioactive exposure to individuals was not performed because the result values were lower than the MDA values. Our results indicate that the study site shows no contamination by the Cs-137 radionuclide.
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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 | 0.000 |
| 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) | 0.000 | 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".