Effect of Organic Matter Additions on Uptake of Weathered DDT by<i>Cucurbita pepo</i>ssp.<i>pepo</i>cv. Howden
Bibliographic record
Abstract
Greenhouse studies were conducted to assess the impact of organic matter additions on plant uptake of DDT [2,2-bis(chlorophenyl)-1,1,1-trichloroethane] from weathered soil. Cucurbita pepo ssp. pepo cv. Howden pumpkins were grown in 100 g of DDT contaminated soil ([DDT] - 1100 ng/g) mixed with equal volumes of either clean soil, perlite, vermiculite, peat, potting soil, or granular activated carbon (GAC) to give total organic carbon contents of 2.4%, 2.5%, 2.6%, 11.5%, 12.2%, and 27.3%, respectively. As in other studies, root DDT concentrations were significantly lower in soils with high organic matter. Root bioaccumulation factors (BAF = [DDT]root/[DDT]soil) approximated this trend. Root concentrations correlated with organic matter concentrations and not with soil DDT concentrations. Conversely, shoot DDT concentrations, shoot BAFs and translocation factors (TLF = BAF(shoot)/BAF(root)) were not significantly different between treatment groups, except for plants grown in GAC/DDT soil. This suggests that amendments with a range of organic matter contents may be added to improve soil conditions at industrial sites without significant adverse effects on phytoextraction potential of C. pepo ssp. pepo.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".