A preliminary study for non-invasive quantification of manganese in human hand bones
Bibliographic record
Abstract
Manganese (Mn) is a nutrient essential for regulating neurological and skeletal functions in the human body, but it is also toxic when humans are excessively exposed to Mn. Blood (or serum/plasma) and other body fluids reflect only the most recent exposure and rapidly return to within normal ranges, even when there has been a temporary excursion in response to exposure. In this context, we have been developing a non-invasive measurement of Mn stored in bone, using in vivo neutron activation analysis. Following feasibility studies, a first pilot study, using neutron activation analysis to measure Mn in the bones of the hand of ten healthy male human subjects, was conducted with the approval of the concerned research ethics boards. The participants of this study had no known history of exposure to Mn. Two volunteers were excluded from this study due to technical problems with their measurements. The inverse variance weighted mean value of Mn/Ca for the participants of this study is 0.12+/-0.68 microg Mn/g Ca which is comparable within uncertainties with the estimated range of 0.16-0.78 microg Mn/g Ca and mean value of 0.63+/-0.30 microg Mn/g Ca derived from cadaver data. It is recommended to investigate the use of the diagnostic technique for in vivo measurements of workers exposed occupationally to excessive amounts of Mn who could develop many-fold increased levels of Mn in bones as demonstrated through various animal studies. The technique needs further development to improve the precision of in vivo measurements in the non-exposed population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".