High‐energy PIXE using very energetic protons: quantitative analysis and cross‐sections
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 Latterly, PIXE using high‐energy protons has been applied effectively for the qualitative analysis of archaeological and art objects, providing information from deep inside the object. This is due to the high cross‐sections for the excitation of K‐lines of heavy elements together with the large penetration depth of high‐energy protons, resulting in analysable depth of up to several millimetres. After the extension of the GUPIX software package to proton energies of up to 100 MeV, quantitative analysis came within reach. Measurements on thin and thick metal targets, and also on alloy standards with known composition and various thickness, were performed. The concentrations obtained were compared with the certified values. The agreement was good for samples with a thickness of around 2 mm. However, for several centimetre thick samples, the heavy elements were overestimated when using the K‐lines of these elements for the data evaluation. To clarify this, K‐shell cross‐section measurements were carried out for various Z . The measurements and the results are presented and discussed. Copyright © 2005 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it