Discovery of 40 Classes of Per- and Polyfluoroalkyl Substances in Historical Aqueous Film-Forming Foams (AFFFs) and AFFF-Impacted Groundwater
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aqueous film-forming foams (AFFFs), containing per- and polyfluoroalkyl substances (PFASs), are released into the environment during response to fire-related emergencies. Repeated historical applications of AFFF at military sites were a result of fire-fighter training exercises and equipment testing. Recent data on AFFF-impacted groundwater indicates that ∼25% of the PFASs remain unidentified. In an attempt to close the mass balance, a systematic evaluation of 3M and fluorotelomer-based AFFFs, commercial products, and AFFF-impacted groundwaters from 15 U.S. military bases was conducted to identify the remaining PFASs. Liquid chromatography quadrupole time-of-flight mass spectrometry was used for compound discovery. Nontarget analysis utilized Kendrick mass defect plots and a "nontarget" R script. Suspect screening compared masses with those of previously reported PFASs. Forty classes of novel anionic, zwitterionic, and cationic PFASs were discovered, and an additional 17 previously reported classes were observed for the first time in AFFF and/or AFFF-impacted groundwater. All 57 classes received an acronym and IUPAC-like name derived from collective author knowledge. Thirty-four of the 40 newly identified PFAS classes derive from electrochemical fluorination (ECF) processes, most of which have the same base structure. Of the newly discovered PFASs found only in AFFF-impacted groundwater, 11 of the 13 classes are ECF-derived, and the remaining two classes are fluorotelomer-derived, which suggests that both ECF- and fluorotelomer-based PFASs are persistent in the environment.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.008 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it