Use of double Göbel mirrors with high-temperature stages for powder diffraction – a strategy to avoid severe intensity fade
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Bibliographic record
Abstract
This paper describes an approach for countering an issue that can occur when using a high-temperature stage with a diffractometer equipped with double Göbel mirrors. The optical characteristics of the dual-mirror configuration make it more susceptible to intensity loss with sample displacement than conventional parallel-beam secondary optics. This issue has been apparent in the use of a high-temperature stage on a diffractometer equipped with dual mirrors, where data could not be obtained from the full room temperature to 1273 K range without resetting the sample height manually part way through the experiment. A simple technique involving controlled contouring of the sample surface has been demonstrated to allow data to be collected uninterrupted over the full temperature range, while retaining satisfactory intensities. The extent to which this technique extends the tolerable sample displacement range has been quantified using a computer-controlled XYZ stage.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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