Straw return enhances the risks of metals in soil?
Bibliographic record
Abstract
Interactions between organic matter (OM) and metals in soils are important natural mechanisms that can mitigate metal bioaccumulation in terrestrial environments. A primary source of OM in soils is straw return, accounting for more than 65% of OM input. Straw-OM has long been believed to reduce metal bioaccumulation, e.g., by immobilizing metals in soils. However, there is growing evidence that straw return could possibly enhance bioavailability and thus risks (i.e., food safety) of some metals in crops, including Cd, Hg, and As. Poor understanding of straw return-induced increases in metal bioavailability would add uncertainty in assessing or mitigating risks of metals in contaminated farming soils. Here, 863 pieces of literature (2000-2019) that reported the effects of straw return on metal bioavailability and bioaccumulation were reviewed. Mechanisms responsible for the increased metal mobility and bioavailability under straw return are summarized, including the effects of dissolution, complexation, and methylation. Effects of straw return on the physiology and the absorption of metals in plants is also discussed (i.e., physiological effect). These mechanisms are then used to explain the observed increases in the mobility, bioavailability, and bioaccumulation of Cd, Hg, and As under straw amendment. Information summarized in this study highlights the importance to re-consider the current straw return policy, particularly in metal-contaminated farmlands.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".