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Record W4414070676 · doi:10.5267/j.ccl.2025.8.008

Estimating the leaching of fenitrothion and thiobencarb in agricultural soils using laboratory lysimeters

2025· article· en· W4414070676 on OpenAlexvenueno aff
Mohamed R. Fouad, Ahmed F. El-Aswad, Maher I. Aly

Bibliographic record

VenueCurrent Chemistry Letters · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFenitrothionLysimeterLeaching (pedology)LoamSoil waterLessivagePesticideLolium multiflorum

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.179

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.239
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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