Phytotoxicity of cerium to cucumbers
Bibliographic record
Abstract
Cerium is one of the most abundant rare earth elements (REE) with an estimated average concentration in the Earth's crust of 66 μg g-1, which is equal to or greater than Ni and Pb. Hydroponic experiments were performed to examine the rhizotoxicity of Ce to cucumber (Cucumis sativa) seedlings and the effects of H+ and Ca2+ were also studied. Ce concentration that causes 50 % reduction in root elongation (IC50) was calculated and the values ranged from 0.29 μM at pH 6.0 with 0.20 mM Ca to > 2.0 μM at pH 4.5 with 2.00 mM Ca. Column leaching experiments were conducted and the partitioning coefficients (Kd) were calculated. Total metal concentrations in soils were measured before and after spiking and metal concentrations in soil solution (leachates) were also measured during 9 days of spiking and leaching. The results suggest that leaching is an important step after spiking soils in order to remove excess dissolved metals. Large Kd values indicate that Ce is strongly bound to soil particles and that the bioavailable Ce could be much lower than the total Ce. Phytotoxicity of Ce was examined by performing pot experiments. Cucumbers were grown in Ce-spiked soils for 14 days and a dose-response relationship was established. The results from the pot experiments suggest that Ce toxicity is similar to Zn and Ni with the IC50 ranging from 100 μg g-1 Ce for root growth to 2630 μg g-1 Ce for biomass. Bioaccumulation of Ce was also observed in Cucumis sativa, however, most Ce was found in the root and much less Ce was transferred to the leaf.
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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) | 0.001 | 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) | 0.001 | 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".