<i>In vivo</i> study of an x-ray fluorescence system to detect bone strontium non-invasively
Bibliographic record
Abstract
An x-ray fluorescence (XRF) system using 125I as the source was developed to measure strontium in bone in vivo. As part of an in vivo pilot study, 22 people were measured at two bone sites, namely the index finger and the tibial ankle joint. Ultrasound measurements were used to obtain the soft tissue thickness at each site, which was necessary to correct the signal for tissue attenuation. For all 22 people, the strontium peak was clearly distinguishable from the background, proving that the system is able to measure Sr in vivo in people having normal bone Sr levels. Monte Carlo simulations were carried out to test the feasibility and the limitations of using the coherently scattered peak at 35.5 keV as a means to normalize the signal to correct for the bone size and shape. These showed that the accuracy of the normalized Sr signal when comparing different people is about 12%. An interesting result arising from the study is that, in the measured population, significantly higher measurements of bone Sr concentration were observed in continental Asian people, suggesting the possibility of a dietary or race dependence of the bone Sr concentration or a different bone biology between races.
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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) | 0.000 | 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) | 0.001 | 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".