Trans-Global Biogeochemistry of Soil to Grain Transport of Arsenic and Cadmium
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Previous studies have shown that arsenic and cadmium can accumulate in rice grain to levels that cause health concerns. Furthermore, geographical survey has shown that there is considerable variation (~ 100-fold) in accumulation of these carcinogens in rice grain. This variance must be due to heterogeneity in soil biogeochemistry and contrasting rice management regimens. Here we present the first systematic global study to investigate the impact of soil biogeochemistry on accumulation of these elements in rice grain. Matched grain, shoot, root and soil samples were collected across a latitudinal gradient from East Africa to Europe and soil, shoot, grain chemistry and soil microbial community (prokaryotes and fungi) assessed within the context of arsenic and cadmium biogeochemistry. European and Vietnamese grain sum of arsenic species (inorganic arsenic plus dimethylarsonic acid) concentration medians, ~ 0.1 mg/kg, were found to be around ten-fold higher compared to those in East Africa and Sri Lanka. Arsenic concentrations were linked to higher levels of soil arsenic, and to higher abundance of soil sulphur-oxidising and sulphate reducing bacteria and methanogenic archaea. For cadmium, Sri Lanka showed highest (median 0.0156 mg/kg) and Europe lowest (median of 0.001 mg/kg) levels in grain, with the other regions showing intermediate values. Interestingly, grain cadmium was unrelated to soil cadmium concentrations, with Europe having the highest levels of cadmium in soil. Instead, grain cadmium correlated with higher oxidation/reduction potential, lower -log[hydrogen ion], lower soil calcium, and to a higher abundance of aerobic bacteria and fungi (lowest abundance of these organisms in European soils).
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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