New statistical calibration approach for Bruker AXS D8 Discover microdiffractometer with Hi-Star detector using <scp>GADDS</scp> software
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Bibliographic record
Abstract
An additional statistical calibration for the Bruker D8 Discover microdiffractometer is necessary to obtain accurate reproducible 2 θ data for cell-refinement work. This new approach uses a graphical mapping method of the 2 θ error versus the location of a selected diffraction peak on the detector surface to describe the separate roles of different calibration procedures (rebiasing, flood field, and spatial corrections) and parameters (sample-to-detector distance, x - y center coordinate) in minimizing the error. Optimized parameters are used to obtain the lowest achievable Δ 2 θ with this setup. Intensity error relative to the position of the diffracted line on the detector was found to be consistent at up to 20% and could not be reduced using any of the investigated techniques and parameters.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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