Bibliographic record
Abstract
Abstract It was hypothesized 110 years ago that substances that dissolve in lipids pass more easily into cells than those that dissolve in water. Thus, weak acids such as glyphosate should more readily pass through the non-polar plant cuticle in the non-dissociated, more non-polar form. The objective of this study was to test this hypothesis in a series of studies in the greenhouse involving three weed species. The pH of the glyphosate spray solution was varied between 1.5 and 6. The glyphosate activity on giant foxtail, common lambsquarters, and velvetleaf (pH) was not affected by pH values between 1.5 and 6 when adjusted with hydrochloric acid (HCl). If diammonium sulfate, was also present, the results were similar; however, the glyphosate activity on velvetleaf was much greater. If the pH was lowered with sulfuric acid, H2SO4, an increase in the glyphosate activity on velvetleaf became evident as the pH was lowered from 6.0 to 1.5. This was attributed to the water conditioning effect of the SO4= in hard water. With tank-mixing glyphosate with 1 % NT®NT (N TANK) is a product of Adjuvants Plus, Kingsville, Ontario, Canada N9Y 255., a proprietary blend of surfactants and monocarbamide, which lowered the pH to 2.0, the water conditioning benefit of NT was decreased on velvetleaf as the pH was raised from 2.0 to 7.0. In summary, the hypothesis was disproved with respect to glyphosate.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".