Childhood Lead Exposure in the Palestinian Authority, Israel, and Jordan: Results from the Middle Eastern Regional Cooperation Project, 1996–2000
Bibliographic record
Abstract
In the Middle East, the major sources of lead exposure have been leaded gasoline, lead-contaminated flour from traditional stone mills, focal exposures from small battery plants and smelters, and kohl (blue color) in cosmetics. In 1998-2000, we measured blood lead (PbB) levels in children 2-6 years of age in Israel, Jordan, and the Palestinian Authority (n = 1478), using a fingerstick method. Mean (peak; percentage > 10 microg/dL) PbB levels in Israel (n = 317) , the West Bank (n = 344), Jordan (n = 382) , and Gaza (n = 435) were 3.2 microg/dL (18.2 ; 2.2%) , 4.2 microg/dL (25.7; 5.2%), 3.2 microg/dL (39.3; < 1%) , and 8.6 microg/dL (> 80.0; 17.2%), respectively. High levels in Gaza were all among children living near a battery factory. The findings, taken together with data on time trends in lead emissions and in PbB in children in previous years, indicate the benefits from phasing out of leaded gasoline but state the case for further reductions and investigation of hot spots. The project demonstrated the benefits of regional cooperation in planning and carrying out a jointly designed project.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".