Collection of Airborne Fluorinated Organics and Analysis by Gas Chromatography/Chemical Ionization Mass Spectrometry
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
The ubiquitous detection of perfluorooctane sulfonate (PFOS) in humans and animals has produced a need for sensitive and compound-specific analytical methods to determine the environmental distribution of fluorinated organic contaminants. A suite of potential PFOS precursors (sulfonamides) and fluorotelomer alcohols (FTOHs) were separated by gas chromatography and detected by chemical ionization mass spectrometry (GC/CI-MS). Full-scan spectra were collected in both positive and negative chemical ionization (PCI and NCI, respectively) mode to determine retention time windows and fragmentation patterns. In selected ion monitoring (SIM) mode, instrumental detection limits ranged from 0.2 to 20 pg for individual analytes, depending on ionization mode. PCI mode was preferred for routine analysis because of the simple mass spectra produced, typified by the presence of a major molecular ion [M + H]+. High-volume air samplers collected gaseous and particle-bound fluoroorganics on composite media consisting of XAD-2, polyurethane foam (PUF), and quartz-fiber filters. The combined collection efficiency for individual analytes was 87 to 136% in breakthrough experiments. Application of the method to the analysis of ambient air from urban and rural sites confirmed the presence of six novel fluorinated atmospheric contaminants at picogram per meter3 concentrations. Low concentrations of fluoroorganics were consistently detected in blanks (<4 pg m(-3)); however, this did not prevent confirmation or quantification of environmental concentrations.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.012 | 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