Determination of acephate and its degradation product methamidophos in soil and water by solid-phase extraction (SPE) and GC-MS
Bibliographic record
Abstract
Acephate and its metabolite, methamidophos, are both highly polar organophosphorus pesticides (OPs) and are therefore highly soluble in water, which leads to difficulties when traditional methods of extraction, such as LLE (liquid–liquid extraction), are used. Solid-phase extraction (SPE) is a relatively new, highly versatile method, which has proven successful in many cases that were considered problematic in the past. In this study, several adsorbents (polymeric and silica based) and parameters are considered and modified to obtain maximum recovery. Maximum recoveries for acephate and methamidophos were found to be 90–95% and 85–90% respectively with Oasis HLB cartridges and methylene chloride as the elution solvent. In order to establish applicability and reliability, the matrix effect of several real water and solid (compost and soil) samples was evaluated. A 20–30% diminution of recovery is noted for some samples with a complex matrix containing a high amount of dissolved organic matter.
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 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 | 0.001 |
| 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 | 0.001 | 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".