Analysis of Perchlorate in Water and Soil by Electrospray LC/MS/MS
Bibliographic record
Abstract
A method has been developed for the determination of perchlorate in water and soil matrixes using electrospray liquid chromatography/mass spectrometry/mass spectrometry. Perchlorate is quantitated by monitoring the ion signal from mass 83, which is formed by a loss of an oxygen atom from the perchlorate molecular ion. The method was developed to be effective and economical in production laboratory analysis of perchlorate in environmental water and soil samples. Data were gathered to define method sensitivity, performance, selectivity, and robustness. Analyte stability, method susceptibility to interferences, and the reliability of the chlorine isotope ratio as an identification tool were examined. The aqueous method detection limit (MDL) is 0.05 microg/L and was determined using an actual groundwater matrix. The soil MDL is 0.5 microg/kg and was determined using Ottawa sand. The stability study was performed by spiking water samples at 0.25, 10, and 20 microg/L and analyzing them 50 days later. Acceptable recoveries were obtained for all samples. The relative standard deviation (RSD) for the replicate analyses in the stability study indicates that the method is capable of RSD values less than 5% in a relatively clean groundwater matrix. The ionization suppression study was performed by spiking water samples containing 1000 mg/L carbonate, chloride, and sulfate with 0.05 and 0.5 microg/L perchlorate and then measuring the recovery of the spike. The results indicate that the procedure does not have significant suppression effects at the high salt levels tested. Calibration, quality control sample, field sample, and suppression study data were combined to examine isotope ratio reliability. The results of that work show that chlorine isotope ratios can be used to define statistical process control limits for use as an additional analyte identification tool.
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 | 0.001 |
| 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 | 0.001 |
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".