A global database of polybrominated diphenyl ether flame retardant congeners in foods and supplements
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
Polybrominated diphenyl ether (PBDE) flame retardants contaminate the food supply yet health effects are uncertain. A global PBDE database was developed to improve diet and disease risk assessments. Congener-specific data from 2002 to 2015 were extracted from 86 articles into a source database representing 32 countries. Geometric mean PBDE concentrations for foods and supplements were derived for 11 congeners individually and combined, and used to calculate means for 27 dietary groups (pg/g ww). Dark or oily fish had the highest data availability, followed by shellfish, eggs, dairy products and dairy fats. Data were less available for white or lean fish, red meat, poultry meat, processed meats, fish oil supplements; 17 groups had very limited data. At the group level, mean ∑11PBDE was extremely high for fish oil supplements (13,862 pg/g) and high for most aquatic groups (462–837 pg/g), poultry liver, poultry fat (1045–1860 pg/g). Moderate groups included white or lean fish, poultry meat, poultry skin, eggs, baked products, red meat fat, red meat liver (115–414 pg/g). Dairy and plant groups had low PBDE concentrations. ∑11PBDE variability was high within most aquatic groups. This database supports assessment of dietary PBDE in multiple jurisdictions and identifies important sources for dietary tool inclusion and analyses.
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) | 0.000 | 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