Bibliographic record
Abstract
The study aimed to examine the effects of glyphosate and 2,4-D herbicides on the reproduction of invitro eiseniafoetida earthworms.This species was chosen because of its easy in-vitro reproduction.The experiment followed a randomized complete block design with four replications.The study included a control treatment, a factory recommended dose treatment (1.5 L/ha 2,4-D, 5 L/ha glyphosate), two overdose treatments (2.25 L/ha 2,4-D, 7.5 L/ha glyphosate), and two underdose treatments (.75 L/ha 2,4-D, 2.5 L/ha glyphosate).The herbicide treatments caused weight loss in eiseniafoetida earthworms.Higher doses of each herbicide resulted in more weight loss.The weight loss effect of the herbicides degraded with time.This was observed for both herbicides in all treatments.After the fifth week, there was a significant difference between the control and the experimental groups.However, there was no significant difference between the experimental groups themselves, which can be related to herbicide degradation.The 2,4-D treatment caused more weight loss compared to the glyphosate treatment because it is a more toxic herbicide.Preliminary analysis indicated that behavioral tests could be used to quickly examine polluted soils.They can also be used as confirmatory analysis to assess the extent of the pollution.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.770 | 0.785 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".