X-Ray Microanalysis in the Environmental SEM Using Mapping and Fourier Deconvolution Techniques
Bibliographic record
Abstract
Abstract X-ray microanalysis of any type of specimen in its natural state without the use of conventional SEM specimen preparation techniques has immense potential in a wide range of scientific and industrial applications. This capability would be particularly useful in microanalysis applications where it is highly desirable to preserve the integrity of the specimen, for example in semiconductor failure analysis and forensic investigations. in principle, this X-ray microanalysis goal can be achieved in an environmental or variable pressure scanning electron microscope (VPSEM) because specimen charging and vacuum stability problems are negated by the presence of a gas in the specimen chamber. However, the accuracy and spatial resolution of X-ray microanalysis in the VPSEM is significantly degraded by the chamber gas as it scatters primary beam electrons, generating spurious X-rays far from the analysis point. to date, two different X-ray measurement strategies have been developed to facilitate X-ray microanalysis at high chamber pressure in the VPSEM.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".