On the Peak to Background Ratio of X-Rays emitted from Rough Surfaces
Bibliographic record
Abstract
Abstract The classical schemes to convert the x-ray intensity into concentration, using the ZAF or the ϕ (ρz ) methods, are valid for specimens having homogeneous composition and flat surfaces. Quantitative schemes have also been developed for x-ray microanalysis of multi-layered specimens. More recently, a quantitative method has been proposed for the microanalysis of spherical inclusions embedded in a matrix as well as Monte Carlo simulations of x-ray emission from porous materials. For the case of specimens having a non-planar surface, a quantitative method based on the peak to background ratio, using photons of the same energy, has been proposed1. However, this method has some pitfalls. First, this method is based on the assumption that the peak to background ratio is independent of the specimen roughness which is not strictly correct because the ionization cross sections and the bremstrallung cross sections are not the same. Therefore, the shapes of the ϕ (p z ) curves are not the same for characteristic and continuum photon of the same energy resulting in different absorption corrections. The result is that the peak to background ratio will vary with beam position on a rough surface.
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How this classification was reachedexpand
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".