Assessment of the effect of strontium, lead and aluminum on dual-energy x-ray absorptiometry and quantitative ultrasound using trabecular bone-mimicking phantoms
Bibliographic record
Abstract
Dual-energy X-ray absorptiometry (DXA) is the gold standard of bone densitometry. However, inaccurate estimation of areal bone mineral density (aBMD) is of concern when calcium in bone mineral is partially substituted with bone-seeking elements such as strontium, lead and aluminum. Quantitative ultrasound (QUS) is an alternative bone densitometry technique that can assess bone health based on the measurement of acoustic parameters. This study aims to investigate the effect of the clinically relevant concentrations of bone-seeking elements on aBMD measured by DXA and the acoustic parameters measured by QUS, using trabecular bone-mimicking phantoms. Statistically significant linear relationship was observed between aBMD and strontium concentration. For clinically relevant concentrations of lead and aluminum, the deviation in aBMD measurements was within 1% coefficient of variation of DXA. No statistically significant deviation was observed in stiffness index measurement by QUS in the presence of any of the three bone-seeking elements
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".