Rapid analysis of organophosphorus pesticides in soils
Bibliographic record
Abstract
An analytical methodology for directly analyzing organophosphorus pesticides (OPPs) in solid matrices was devised around a multigram capacity direct insertion probe (DIP) interfaced to a quadrupole mass spectrometer (MS). The DIP-MS system was used to analyze acephate [O,S-dimethyl acetylphosphoramidothioate] and diazinon [O,O-diethyl-O-(2-isopropyl-6-methyl-4-pyrimidinyl)phosphorothioate] in a clean sand matrix, namely, Ottawa sand. Diazinon was also analyzed in a Florida spodosol, Immokalee soil. Instrument detection limit studies demonstrate that the DIP-MS system is capable of detecting 5 g of acephate in the absence of an interfering matrix. The method detection limit for diazinon was calculated at 2.5 g. DIP-MS analysis of diazinon in the Immokalee soil showed as much as a 50% reduction in instrument response compared to the relatively pure Ottawa sand. This was attributable to the dilution effect of codesorbing soil organic matter. Results from the performance evaluation studies using Immokalee soil demonstrate the potential of the DIP-MS technique to directly analyze OPPs and other thermally extractable chemicals in soils and other solid matrices without the need for solvent extraction, sample pretreatment, or confirmation by other analytical methods.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".