Combining the Reverse Monte Carlo and the Rietveld Glass Structure Modelling Methods
Bibliographic record
Abstract
Abstract The Reverse Monte Carlo (RMC) method involves usually at least one thousand atoms, and modelling may start from random atomic positions. The Rietveld for disordered material (RDM) method needs a crystal structure as a starting mean model, with hardly more than 25 independent atoms. The two methods are reconciled when a satisfying RDM model, enlarged by multiplying the cell axes, is subjected to random moves by the RMC method. Three examples are presented: glassy SiO2, ZnCl2 and NaPbM2F9 (M = Fe, V). Coordinations were constrained (SiO4 and ZnCl4 tetrahedra; MF6 octahedra), so that the final RMC models keep essentially the crystal structure features of the RDM starting models, being the phases in which devitrify the glasses, in all cases. 1.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".