Electron microprobe analysis under conditions of non-normal Electron beam incidence
Bibliographic record
Abstract
Abstract From its inception, electron microprobe analysis was almost exclusively done under conditions of normal electron probe incidence. The radial symmetry of this geometry greatly simplified the development of quantitative equations, and these equations where further refined based on large amounts of data also collected at normal incidence. However, as x-ray detection systems where added to scanning electron microscopes (SEMs), samples were often viewed under conditions of non-normal incidence and attempts were made to modify the various correction procedures to give acceptable quantitative results. Little justification for these methods has ever been published and so the current study was undertaken to compare theoretically calculated x-ray emission from a well characterized sample, in this case NiAl (.685 wt. % Ni,.315 wt. %A1) with experimentally measured results collected as a function of tilt angle. The theoretical calculation where done using a Monte Carlo (MC) program developed by Gauvin and Lifshin.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.004 | 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".