Human biomonitoring initiative (HBM4EU): Human biomonitoring guidance values (HBM-GVs) derived for cadmium and its compounds
Bibliographic record
Abstract
The methodology agreed within the framework of the HBM4EU project is used in this work to derive HBM-GVs for the general population (HBM-GVGenPop) and for workers (HBM-GVWorker) exposed to cadmium (Cd) and its compounds. For Cd, a significant number of epidemiological studies with dose–response relationships are available, in particular for kidney effects. These effects are described in terms of a relation between urinary Cd (U-Cd) or blood Cd (B-Cd) levels and low molecular weight proteinuria (LMWP) markers like beta-2-microglobulin (β2M) and retinol-binding protein (RBP). In order to derive HBM-GVs for the general population and workers, an assessment of data from evaluations conducted by national or international organisations was undertaken. In this work, it appeared relevant to select renal effects as the critical effect for the both groups, however, differences between general population (including sensitive people) and workers (considered as an homogenous population of adults who should not be exposed to Cd if they suffer from renal diseases) required the selection of different key studies (i.e. conducted in general population for HBM-GVGenPop and at workplace for HBM-GVWorker). For U-Cd, a HBM-GVGenPop of 1 µg/g creatinine (creat) is recommended for adults older than 50 years, based on a robust meta-analysis performed by EFSA (EFSA, 2009a). To take into account the accumulation of Cd in the human body throughout life, threshold or ‘alert’ values according to age were estimated for U-Cd. At workplace, a HBM-GVWorker of 2 μg/g creat is derived from the study of Chaumont et al., (2011) for U-Cd, and in addition to this recommendation a HBM-GVworker for B-Cd of 5 µg/L is also proposed. The HBM-GVWorker for U-Cd is similar to the biological limit value (BLV) set by the new amendment of the European Carcinogens and Mutagens Directive in June 2019 (2 µg/g creat for U-Cd).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".