Geometrical parameterization of the crystal chemistry of<i>P</i>63/<i>m</i>apatite. II. Precision, accuracy and numerical stability of the crystal-chemical Rietveld refinement
Why this work is in the frame
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Bibliographic record
Abstract
A script developed for crystal-chemical Rietveld refinement of P 6 3 / m apatite with TOPAS is implemented in parallel with standard structure refinement. Least-squares standard uncertainty (s.u.) values for directly extracted crystal-chemical parameters are nearly an order of magnitude lower than those obtained indirectly by analysis of atom coordinates derived by standard Rietveld refinement. This amazing finding originates partly in the reduction of the number of refinement parameters from 21 to 17 and partly in the fact that cell data now derive from crystal-chemical parameters instead of vice versa . Great precision and accuracy otherwise funneled into unit-cell parameters is then more distributed among mostly crystal-chemical distance parameters. The least-squares s.u. values are supported by analysis of numerous refinements of the same experimental data with added artificial intensity noise. Structural parameters from single-crystal results agree better with those extracted by crystal-chemical refinement. On the basis of singular value decomposition analyses performed using the program SVDdiagnostic [Mercier et al. (2006). J. Appl. Cryst. 39 , 458–465], crystal-chemical and standard Rietveld refinements are shown to have similar numerical stability. Crystal-chemical parameters extracted by direct Rietveld refinement, therefore, are more precise than, more accurate than and numerically as reliable as those derived from analysis of regular crystallographic refinement of the same data.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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