Evaluation of MCNP5 and EGS4 for the simulation of <i>in vivo</i> strontium XRF measurements
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
Abstract In order to optimize x‐ray fluorescence (XRF) experiments, Monte Carlo (MC) simulations provide a valuable tool that allows different system setups and experimental conditions to be explored in a controlled way. Electron gamma shower (EGS4) and Monte Carlo N‐Particle5 (MCNP5) are two widely used MC programs that simulate the photon and electron transport in great detail and allow for the simulation of an arbitrary experimental geometry. Tested in 2001 by Al‐Ghorabie et al. , earlier versions of these programs failed in reproducing the outcome of a platinum XRF in vivo measurement. The authors found that the discrepancy between measured and simulated results could be attributed to the free electron approximation made by the programs in simulating the Compton scattering. More recent versions of EGS4 and MCNP have updated their treatment for photon transport at low energies and have included Doppler broadening in the Compton profile. In this study we test the capability of these new versions of EGS4 and MCNP in reproducing the outcome of an in vivo strontium XRF measurement. Copyright © 2007 John Wiley & Sons, Ltd.
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 | 0.003 | 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 | 0.000 | 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