Estimating the leaching of fenitrothion and thiobencarb in agricultural soils using laboratory lysimeters
Bibliographic record
Abstract
The total amount of iodide applied was recovered from all lysimeters in symmetrical curves. Fenitrothion-BTCs included two peaks, while thiobencarb-BTCs included one peak in the two tested soil types. The cumulative of fenitrothion (75.3%) and thiobencarb (75.8%) from sandy clay loam soil-lysimeter were significantly higher compared with that of fenitrothion (21.1%) and thiobencarb (60.9%) from clay soil-lysimeter. Also, in clay soil-lysimeters, thiobencarb was more leaching (60.9%) compared to fenitrothion (21.1%). Nevertheless, in the sandy-lysimeter, the cummulative amounts of both compounds were almost the same (75.5%). Thiobencarb was more leaching and more rapidly in clay soil than fenitrothion. Whereas the leaching of the two compounds was almost the same in sandy clay loam soil. However, the leaching of thiobencarb was the fastest one. Fenitrothion required more water (about twice) for leaching from the two tested soil types compared to thiobencarb. Leaching statistics are needed to manage environmental protection and keep pesticides from reaching groundwater, as well as to anticipate and comprehend the behavior of pesticides in various soil types.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".