Investigating coherent normalization and dosimetry for the <sup>241</sup> Am-La K XRF system
Bibliographic record
Abstract
Abstract Objectives : Lanthanum (La) retention in bone has been shown to occur in individuals who are orally administered lanthanum carbonate (LaC), a drug to treat hyperphosphatemia. The breakdown of LaC in the gastrointestinal tract into La 3+ and carbonate ions results in residual quantities of La being deposited in bone. We previously reported on a non-invasive x-ray fluorescence (XRF) system that was developed to quantify bone La concentrations and applied it to a series of excised cadaver tibiae. However, given interpatient variability in bone shape and size, differential signal attenuation that occurs in bone and tissue, patient movement and overlying tissue thickness at the measurement site, quantifying bone La concentrations during in vivo measurements in live subjects needs to be investigated further along with the radiation dose associated with the measurement. Approach : Coherent normalization was investigated as a function of overlying tissue thickness, source-subject distance and bone radius through Monte Carlo simulation and experimental work. This was accomplished by observing the ratio of the net La K x-ray peak area to the coherently scattered peak area at 59.5 keV. In addition, the dose delivered during a 2000 s measurement was determined using radiochromic film. Main results : The coherent normalization of the La x-ray signal was shown to be independent of overlying tissue thickness, source-subject movement and bone radius, which indicates that this normalization procedure can correct for these factors. The equivalent skin dose and effective dose were 18.0 mSv and 3.2 μSv, respectively for a five-year-old. Significance : While coherent normalization for the bone lead (Pb) and bone gadolinium (Gd) systems has been shown to be successful, we also report that this normalization procedure can correct for these interpatient variabilities in the in vivo 241 Am-La K XRF system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".