Effects of surfactants on rhizodegradation of oil in a contaminated soil
Bibliographic record
Abstract
The effects of nonionic surfactants on degradation of engine oil in metal contaminated soil using Indian mustard (Brassica juncea) were investigated. Triton X-100 and Tween 80 were individually applied to test pots in which the soil had been earlier spiked with 500 mg kg(-1) of used engine oil, 500 mg kg(-1) of PbCl(2) and 50 mg kg(-1) of CdCl(2). For he application of Tween 80 to the soil, the fractions of rhizodegraded oil and the fractions of removed metals from the soil were well correlated. On the other hand, such a correlation did not exist between the fractions of rhizodegraded oil and the fractions of removed metals for the application of Triton X-100 to the soil. It was observed that Triton X-100 caused a significant decrease in basal soil respiration (BSR) which can be attributed to a reduction in microbial activity. This, in turn, resulted in a reduction of the rhizodegraded oil fraction. Tween 80 proved to be effective in the rhizodegradation of oil under aerobic conditions. Further, this surfactant seems to have the positive effect on the soil microbial population when viewed in terms of BSR.
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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) | 0.000 | 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 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".