Exposome-Explorer 2.0: an update incorporating candidate dietary biomarkers and dietary associations with cancer risk
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
Exposome-Explorer (http://exposome-explorer.iarc.fr) is a database of dietary and pollutant biomarkers measured in population studies. In its first release, Exposome-Explorer contained comprehensive information on 692 biomarkers of dietary and pollution exposures extracted from the analysis of 480 peer-reviewed publications. Today, Exposome-Explorer has been further expanded and contains a total of 908 biomarkers. Two additional types of information have been collected. First, 185 candidate dietary biomarkers having 403 associations with food intake (as measured by metabolomic studies) have been identified and added. Second, 1356 associations between dietary biomarkers and cancer risk in epidemiological studies, which were collected from 313 publications, have also been added to the database. Classifications for both foods and compounds have been revised, and new classifications for biospecimens, analytical methods and cancers have been implemented. Finally, the web interface has been redesigned to significantly improve the user experience.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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