A Pilot Survey of Legacy and Current Commercial Fluorinated Chemicals in Human Sera from United States Donors in 2009
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
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.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it