Review of pollutant lead decline in urban air and human blood: A case study from northwestern Europe
Bibliographic record
Abstract
A review of the transient decline of pollutant lead in the air (Pb A ) and the blood (Pb B ) has been conducted in order to assess the relationship between these environmental reservoirs. We have demonstrated that Pb A decreased 20 to 100 times more than Pb B for the past 30 years, suggesting another significant intake besides airborne lead to explain lead accumulated in humans. This trend has also been observed in two blood surveys we have completed in 1976–1978 and 2008–2009 in northern France and Belgium. Nowadays, the mean Pb B (1.5–3.5 μg/dL) remains at least 100 times higher than the estimated non-contaminated Pb B . Lead isotope imprints in blood could help decipher specific contamination cases, and were coherent with the decline of Pb A , but could not help discriminate the source of blood lead owing to the lack of source imprints, especially from dietary intakes. Correlations between recent Pb B , isotopic imprints and the age of the subjects suggested that lead released from bones has become a significant source of lead in blood. The significant cause for human exposure to lead may have shifted from direct pollutant lead input accumulated in exogenous reservoirs (air and diet) to endogenous lead release from bone tissues consequential to metabolic calcium homeostasis and bone turnover.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".