Rapid analysis of organophosphorus pesticides in soils
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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 μg of acephate in the absence of an interfering matrix. The method detection limit for diazinon was calculated at 2.5 μg. 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.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.012 | 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 it