Optimization of L‐shell X‐ray fluorescence detection of lead in bone phantoms using synchrotron radiation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Closely related toxicity and retention mechanisms of lead (Pb) in the human body involve the bone tissues where Pb can accumulate and reside on a time scale ranging from years to tens of years. In vivo measurements of bone Pb can, therefore, play an important role in a comprehensive health risk assessment of Pb exposure. In vivo L‐shell X‐ray fluorescence (LXRF) measurement of bone Pb was first demonstrated over 4 decades ago. Implementation of the method, however, encountered challenges associated with low sensitivity and calibration procedure. In this study, the LXRF measurement was optimized by varying the incident photon energy and the excitation‐detection geometry. The Canadian Light Source synchrotron radiation was used to compare 2 different excitation‐detection geometries of 90 ° and 135 ° using 3 different X‐ray photon energies: 15.8, 16.6, and 17.5 keV. These energies optimized excitation of the L 3 subshell of Pb and simulated the most intense K‐shell emissions of zirconium, niobium, and molybdenum, respectively. Five rectangular plaster‐of‐Paris bone phantoms with Pb concentrations of 0, 7, 17, 26, and 34 μg/g, and one rectangular 3.1‐mm‐thick resin phantom mimicked the X‐ray attenuation properties of human bone and soft tissue, respectively. Optimal LXRF detection was obtained by the 15.8‐keV energy and the 90 ° and 135 ° geometries for the bare bone and the bone and soft tissue phantoms, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it