A Pilot Survey of Legacy and Current Commercial Fluorinated Chemicals in Human Sera from United States Donors in 2009
Bibliographic record
Abstract
Human biomonitoring has traditionally focused on analyzing the perfluorocarboxylates (PFCAs) and perfluorosulfonates (PFSAs), although the presence of other unidentified fluorinated chemicals has been demonstrated through total organofluorine analysis. Exposure to legacy and current commercial fluorinated chemicals was investigated by analyzing fifty human sera samples collected in 2009 from the United States for forty fluorinated analytes that included the polyfluoroalkyl phosphate diesters (diPAPs), N-ethyl perfluorooctanesulfonamidoethanol-based polyfluoroalkyl phosphate diester (SAmPAP), one fluorotelomer mercaptoalkyl phosphate diester congener (FTMAP), fluorotelomer sulfonates (FTSs), perfluorophosphonates (PFPAs), and perfluorophosphinates (PFPiAs). DiPAP concentrations (0.035-0.136 μg/L) for the more dominant congeners (6:2, 6:2/8:2, 8:2) were lower than those reported in human sera samples collected in 2004, 2005, and 2008. The SAmPAP and 6:2 FTMAP were not detected, but exposure to SAmPAP was suggested based on the detection of one of its potential degradation intermediates, N-ethyl perfluorooctanesulfonamidoacetate (N-EtFOSAA). PFPiAs were detected for the first time in human sera, with C6/C6 and C6/C8 PFPiAs as the dominant congeners, observed in >50% of the 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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".