Liquid Chromatography/Electrospray Ionization/Isotopic Dilution Mass Spectrometry Analysis of n-(Phosphonomethyl) Glycine and Mass Spectrometry Analysis of Aminomethyl Phosphonic Acid in Environmental Water and Vegetation Matrixes
Bibliographic record
Abstract
A liquid chromatography/electrospray/mass spectrometry (LC/ES/MS) method was developed for the analysis of glyphosate (n-phosphonomethyl glycine) and its metabolite, aminomethyl phosphonic acid (AMPA) using isotope-labelled glyphosate as a method surrogate. Optimized parameters were achieved to derivatize glyphosate and AMPA using 9-fluorenylmethyl chloroformate (FMOC-Cl) in borate buffer prior to a reversed-phase LC analysis. Method spike recovery data obtained using laboratory and real world sample matrixes indicated an excellent correlation between the recovery of the native and isotope-labelled glyphosate. Hence, the first performance-based, isotope dilution MS method with superior precision, accuracy, and data quality was developed for the analysis of glyphosate. There was, however, no observable correlation between the isotope-labelled glyphosate and AMPA. Thus, the use of this procedure for the accurate analysis of AMPA was not supported. Method detection limits established using standard U.S. Environmental Protection Agency protocol were 0.06 and 0.30 microg/L, respectively, for glyphosate and AMPA in water matrixes and 0.11 and 0.53 microg/g, respectively, in vegetation matrixes. Problems, solutions, and the method performance data related to the analysis of chlorine-treated drinking water samples are discussed. Applying this method to other environmental matrixes, e.g., soil, with minimum modifications is possible, assuring accurate, multimedia studies of glyphosate concentration in the environment and the delivery of useful multimedia information for regulatory applications.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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 teacher head, 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".