Occurrence and trends of fluorinated pesticides in food commodities marketed in Luxembourg (2011–2024)
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
This study investigated fluorinated pesticide residues in food commodities marketed in Luxembourg, focusing on substances listed in the European Chemicals Agency's Annex XV Restriction Report Proposal as potential precursors of trifluoroacetic acid (TFA), a persistent degradation product of concern. From 6,034 samples collected between 2011 and 2024, 48.1% contained quantifiable residues, with fluorinated compounds detected in 12.3% of the samples. Tea (65.3%) and dried fruits (45.6%) showed the highest contamination rates. Detection rates of fluorinated pesticide residues rose from 9.6% of the samples in 2011 to 26.8% in 2024. In 18 cases (1.8%) EU maximum residue limits (MRLs) were exceeded. Thirty-one distinct fluorinated pesticides were identified, with six compounds, fluopyram, lambda-cyhalothrin, trifloxystrobin, bifenthrin, fluopicolide, and flonicamid accounting for nearly 80% of the detections, all being considered potential precursors of TFA. These findings underline the need for continued monitoring and regulatory attention to limit environmental and health risks from TFA formation.
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 | 0.000 |
| 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 it