Blood Lead Levels in Children 5 to 7 Years of Age from the Republic of Georgia: A Feasibility Study on Lead Surveillance Using Volumetric Absorptive Microsampling
Bibliographic record
Abstract
BACKGROUND: For years, children in the Republic of Georgia, have experienced elevated blood lead levels (BLLs). From September 2023 to April 2024, the National Center for Disease Control and Public Health in Georgia piloted a national surveillance program for lead in children in two western regions of the country, using volumetric absorptive microsampling (VAMS) to measure BLLs. OBJECTIVES: We monitored BLLs and assessed predictors of elevated BLLs in children 5-7 years of age from two regions in the Republic of Georgia. We also aimed to demonstrate the feasibility of VAMS for BLL surveillance. METHODS: in Georgia. RESULTS: . DISCUSSION: Our findings confirm that lead exposure remains a significant public health issue in two regions of the Republic of Georgia, despite a national decrease in BLLs over the past 5 years. To our knowledge, this research marks the first large-scale application of VAMS technology for national BLL surveillance, offering significant advantages as a less invasive lead testing method that is accurate and suitable for settings with limited resources to handle, store, and transport venous blood samples. https://doi.org/10.1289/EHP15788.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".