Glyphosate (Ab)sorption by Shoots and Rhizomes of Native versus Hybrid Cattail (Typha)
Bibliographic record
Abstract
Wetlands in the Prairie Pothole Region of North America are integrated with farmland and contain mixtures of herbicide contaminants. Passive nonfacilitated diffusion is how most herbicides can move across plant membranes, making this perhaps an important process by which herbicide contaminants are absorbed by wetland vegetation. Prairie wetlands are dominated by native cattail (Typha latifolia) and hybrid cattail (Typha x glauca). The objective of this batch equilibrium study was to compare glyphosate absorption by the shoots and rhizomes of native versus hybrid cattails. Although it has been previously reported for some pesticides that passive diffusion is greater for rhizome than shoot components, this is the first study to demonstrate that the absorption capacity of rhizomes is species dependent, with the glyphosate absorption being significantly greater for rhizomes than shoots in case of native cattails, but with no significant differences in glyphosate absorption between rhizomes and shoots in case of hybrid cattails. Most importantly, glyphosate absorption by native rhizomes far exceeded that of the absorption occurring for hybrid rhizomes, native shoots and hybrid shoots. Glyphosate has long been used to manage invasive hybrid cattails in wetlands in North America, but hybrid cattail expansions continue to occur. Since our results showed limited glyphosate absorption by hybrid shoots and rhizomes, this lack of sorption may partially explain the poorer ability of glyphosate to control hybrid cattails in wetlands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".