Phytoremediation of CR(VI) by <i>Spirodela polyrrhiza</i> (L.) Schleiden Employing Reducing and Chelating Agents
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
Phytoremediation of Cr(VI) by Spirodela polyrrhiza in binary combinations with low molecular weight organic compounds (LMWOCs) with a reducing or chelating potential, viz., ascorbic acid, citric acid, tartaric acid, oxalic acid, lactic acid, and glycerol was studied in Cr(VI) containing hydroponic media. Significant increase in the relative dry weight of plants with respect to Cr(VI) treated controls was observed with ascorbic acid and glycerol. The uptake of chromium by S. polyrrhiza followed Michaelis-Menten kinetics of active ion uptake. Interaction between Cr and ascorbic acid, oxalic acid, and lactic acid decreased Cr uptake, whereas citric acid, glycerol, and tartaric acid increased it. Supplementation of LMWOCs to Cr(VI) containing media decreased the MDA content of the plants. Multiple regression models revealed that LMWOCs decrease lipid peroxidation independently, as well as that induced by Cr(VI). It was found that superoxide dismutase (SOD), guaiacol peroxidase (GPX), and catalase (CAT) activities were increased significantly in plants growing in media containing Cr(VI). The study established that lactic acid, citric acid, ascorbic acid, and glycerol were most effective in increasing the Cr(VI) phytoremediating potential of S. polyrrhiza and LMWOCs with reducing or chelating properties decrease Cr(VI) stress in S. polyrrhiza.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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