P-368 Occupational Biological Limit derivation process and Biological Limit Values for several priority substances
Bibliographic record
Abstract
<h3>Introduction</h3> Biomonitoring and atmospheric metrology are complementary approaches to assess occupational exposure to chemicals. The ANSES working group on biomarkers of exposure (WGBME) has developed an approach to derive Biological Limit Value (BLV) for occupational priority substances. <h3>Objectives</h3> The aim of this commuication is to present the approach as we as the derived BLV for the priotity substances. <h3>Methods</h3> Based on available data and using a decision tree, 4 types of BLV may be derived: a BLV based on a health effect for substances with threshold effects, a BLV based on an Occupational Exposure Limit (OEL), a BLV based on a cancer risk level (10–4, 10–5 or 10–6) or a theoretical value called ‘pragmatic BLV’. When knowledge on the relationship biomarker-health effects or biomarker-exposure is lacking, no BLV is derived. Whenever possible, a Biological Reference Value (BRV) based on the 95th percentile of a non-occupationally exposed population is also proposed. BRVs are not risk-based but are part of the preventer’s toolbox. <h3>Results</h3> Since 2011, 16 substances were assessed by the ANSES WGBME. Detailed information has been published in scientific reports which are publicly available on the ANSES website. Lead and Cadmium were the only chemicals for which BLVs based on relationship between health effect and biological levels were derived: lead BLV of 180 μg.L-1 based on neurological effects and urinary cadmium (5 μg.g-1 creatinine) and blood cadmium (4 μg.L-1) based on nephrotoxicity. BLVs (urinary concentrations) based on OELs were derived for cobalt (5 μg.g-1 creatinine), dichloromethane (0.2 mg.L-1) and styrene (40 μg.L-1). A pragmatic BLV based on OEL was calculated for chromium VI (2.5 μg.L-1). No BLV was based on cancer risk level. In addition, no BLVs but BRVs were proposed for substances such as acrylamide, beryllium, butadiene and some phtalates. <h3>Conclusion</h3> This expertise from the ANSES WGBME has led to derive several BLV to prevent health effects in workers or to control exposure to contaminants. BLV and BRV help occupational physician to unfold prevention program and surveillance in occupational settings.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".