Speciation and distribution of arsenic and localization of nutrients in rice grains
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Arsenic (As) contamination of rice grains and the generally low concentration of micronutrients in rice have been recognized as a major concern for human health. Here, we investigated the speciation and localization of As and the distribution of (micro)nutrients in rice grains because these are key factors controlling bioavailability of nutrients and contaminants. Bulk total and speciation analyses using high-pressure liquid chromatography (HPLC)-inductively coupled plasma mass spectrometry (ICP-MS) and X-ray absorption near-edge spectroscopy (XANES) was complemented by spatially resolved microspectroscopic techniques (micro-XANES, micro-X-ray fluorescence (micro-XRF) and particle induced X-ray emission (PIXE)) to investigate both speciation and distribution of As and localization of nutrients in situ. The distribution of As and micronutrients varied between the various parts of the grains (husk, bran and endosperm) and was characterized by element-specific distribution patterns. The speciation of As in bran and endosperm was dominated by As(III)-thiol complexes. The results indicate that the translocation from the maternal to filial tissues may be a bottleneck for As accumulation in the grain. Strong similarities between the distribution of iron (Fe), manganese (Mn) and phosphorus (P) and between zinc (Zn) and sulphur (S) may be indicative of complexation mechanisms in rice grains.
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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 | 0.000 |
| 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 it