The decrease in population bone lead levels in Canada between 1993 and 2010 as assessed by<i>in vivo</i>XRF
Bibliographic record
Abstract
Objective and Approach: A study, conducted in Toronto, Canada, between 2009 and 2011, measured the bone lead concentrations of volunteers aged 1-82 years using in vivo x-ray fluorescence (XRF) technology. MAIN RESULTS: Bone lead levels were lower compared to Ontario in vivo XRF studies from the early 1990s. In adults, the slope of tibia lead content versus age was reduced by 36-56%, i.e. bone lead levels for a given age group were approximately half compared to the same age group 17 years prior. Further, bone lead levels of individuals fell over that time period. In 2010, an average person aged 57 years had a bone lead level approximately 1/3 less than their bone lead level age 40 years in 1993. Using this data, the half-lives of lead in the tibia were estimated as 7-26 years. Tibia lead levels were found to be low in children. The reduction in bone tibia content in children was not significant (p = 0.07), but using data from additional north eastern US studies, there is evidence that childhood tibia stores are lower than in the 1990s. SIGNIFICANCE: In vivo XRF analysis shows that there has been a reduction in the level of lead in bone in Canada over the last two decades. Public health measures have been very successful in reducing ongoing exposure to lead and in reducing bone lead stores.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".