Transformation and binding of <sup>13</sup> C and <sup>14</sup> C‐labelled atrazine in relation to straw decomposition in soil
Bibliographic record
Abstract
Summary As a source of organic matter, crop residues affect the behaviour of pesticides in agricultural soils. The fate of [U‐ring‐ 13 C] and [U‐ring‐ 14 C] atrazine (6‐chloro‐N‐ethyl‐N‐isopropyl‐1,3,5‐triazine‐2,4‐diamine) was investigated during laboratory incubation under controlled conditions in a loamy soil amended with wheat straw at two different states of decomposition: no preliminary decomposition or 6 months’ preliminary decomposition. After 3 months, non‐extractable, so‐called ‘bound’, 13 C‐atrazine residues were recovered in three particle‐size fractions (> 200, 50–200 and < 50 μm), and investigated with solid‐state 13 C‐NMR spectroscopy. Parallel incubations with [U‐ring‐ 14 C] atrazine were carried out to quantify the bound residues as well as the extractable and mineralized fractions. The effect of straw residues on atrazine behaviour depended on whether they had been previously decomposed or not. When straw was decomposed for 6 months prior to incubation, atrazine mineralization was enhanced to 50% of the initial 14 C in contrast to 15% of the initial 14 C in soil alone and soil amended with fresh straw. In parallel, atrazine bound residues were formed in greater amount representing up to 20% of the initial 14 C. CP/MAS 13 C‐NMR on soil size fractions of soil–straw mixtures after incubation with 13 C‐atrazine showed that bound residues contained mostly triazinic C, corresponding to atrazine or primary metabolites. Non‐humified organic materials recovered in size fractions > 200 and 50–200 μm contained significant amounts of bound residues, especially when straw was added to the soil. CP/MAS 13 C‐NMR analysis of humic acids obtained from < 50‐μm fractions was difficult due to overlapping of the native carboxyl 13 C signal with the 13 C‐atrazine signal.
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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 | 0.000 | 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".