<i>In vivo</i>measurement of lead in the bones of smelter workers using the four-element ‘clover-leaf’ geometry detector system
Bibliographic record
Abstract
A total of 497 smelter employees from New Brunswick participated in a bone lead survey conducted by McMaster University in 2008 to examine the efficiency of lead exposure control programmes and a four-element 'clover-leaf' geometry detector system. Nearly 42% of the subjects had participated in both the previous surveys performed in 1994 and 1999. After developing the clover-leaf geometry system in 2006, the reliability of the system based on examining the consistency of four detectors and improving the minimum detection limit (MDL) was tested for the first time in 2008 by measuring lead levels of a large population that was occupationally exposed to lead. The Z test was used to study the distribution of the lead concentration calculated based on K(α) and K(β) lead x-rays, where the results were broadly consistent with a normal distribution criterion, with relatively small means and standard deviations of between 1 and 2. The MDL of the clover-leaf geometry system was improved on average for tibia and calcaneus by a factor of 3.1 compared to the 1999 and 1994 surveys in which a conventional system (one detector) was used. Furthermore, by comparing the results of the three mentioned surveys, the 2008 results were found to represent the highest precision.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".