THE STRUCTURAL ROLE OF EXCESS Cu AND Pb IN GLADITE AND KRUPKAITE BASED ON NEW REFINEMENTS OF THEIR STRUCTURE
Bibliographic record
Abstract
Crystal structures of stoichiometric gladite (empirical formula Cu1.32Pb1.37Bi6.65S12.03) and krupkaite (empirical formula Cu2.00Pb2.03Bi5.99S12.04) from Felbertal, Austria, were refined to R1 = 0.045 and 0.037, respectively, yielding improved positional parameters and interatomic distances. Structures of “oversubstituted ” gladite with an excess of Pb + Cu substitution for Bi + tetrahedral vacancy (empirical formula Cu1.55Pb1.59Bi6.43S12.02, percentage of the aikinite end-member, naik = 39), of “undersubstituted ” krupkaite (Cu1.85Pb1.92Bi6.12S12.06, naik = 47), and of “oversubstituted ” krupkaite (Cu2.32Pb2.40Bi5.64S12.16, naik = 59) from the same locality, were refined to the R1 values of 0.041, 0.051, and 0.052, respectively. Additional copper (occupancy 0.22) forms a broadly zig-zag pattern in each 1 subcell of gladite. In “undersubstituted ” krupkaite (naik = 47), the regular Cu position (Cu 1) was found to be slightly undersaturated. The “oversubstituted ” krupkaite (naik = 59) contains additional Cu, located in the Cu 2 sites situated half-way between the fully occupied Cu 1 positions. Fixing their occupancy to 0.18, in agreement with EPMA data, and refining the adjacent large cation sites as two sites, with 0.18 Pb and 0.82 Bi, respectively, yielded the final model refined here. Interatomic distances and other characteristics of the polyhedra are used to evaluate the effects of cation substitution.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".