Direct-inject suppressed ion chromatography-mass spectrometry method with online preconcentration for short- and ultra short-chain perfluoroalkyl carboxylic acids in fresh water
Bibliographic record
Abstract
This work developed a novel analytical method to detect short- and ultra-short chain perfluoroalkyl carboxylic acids (PFCAs) in freshwater samples by direct injection using ion chromatography mass spectrometry (IC-MS). Ultra-short chain PFCAs, including trifluoroacetic acid (TFA), are often present in aqueous environments at higher concentrations than the longer chain PFCAs, however there are currently a limited number of methods that can analyze them. Detection limits ranged between 1.3 – 2.8 ng/L of the PFCAs (C2 – C6) analyzed and were comparable to other LC-MS and GC-MS methods. The precision of this method ranged from 0.4 – 7.6% for all the PFCAs (C2 – C6). An advantage of this method is small samples sizes under 1 mL can be used. This method was applied to real freshwater samples which included tap water, precipitation, lake water, and river water. TFA was detectable in most of the samples with online pre-concentration and no other additional pretreatment sample preparation. A new unidentified isobaric interferent for TFA was present in most of the freshwater samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".