Matrix Normalized MALDI-TOF Quantification of a Fluorotelomer-Based Acrylate Polymer
Bibliographic record
Abstract
The degradation of fluorotelomer-based acrylate polymers (FTACPs) has been hypothesized to serve as a source of the environmental contaminants, perfluoroalkyl carboxylates (PFCAs). Studies have relied on indirect measurement of presumed degradation products to evaluate the environmental fate of FTACPs; however, this approach leaves a degree of uncertainty. The present study describes the development of a quantitative matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry method as the first direct analysis method for FTACPs. The model FTACP used in this study was poly(8:2 FTAC-co-HDA), a copolymer of 8:2 fluorotelomer acrylate (8:2 FTAC) and hexadecyl acrylate (HDA). Instead of relying on an internal standard polymer, the intensities of 40 poly(8:2 FTAC-co-HDA) signals (911-4612 Da) were normalized to the signal intensity of a matrix-sodium cluster (659 Da). We termed this value the normalized polymer response (P(N)). By using the same dithranol solution for the sample preparation of poly(8:2 FTAC-co-HDA) standards, calibration curves with coefficient of determinations (R(2)) typically >0.98 were produced. When poly(8:2 FTAC-co-HDA) samples were prepared with the same dithranol solution as the poly(8:2 FTAC-co-HDA) standards, quantification to within 25% of the theoretical concentration was achieved. This approach minimized the sample-to-sample variability that typically plagues MALDI-TOF, and is the first method developed to directly quantify FTACPs.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".