CHARACTERIZATION OF GADOLINITE-GROUP MINERALS USING CRYSTALLOGRAPHIC DATA ONLY: THE CASE OF HINGGANITE-(Y) FROM CUASSO AL MONTE, ITALY
Bibliographic record
Abstract
Important data concerning chemical composition of a mineral of the gadolinite group can be obtained from a refinement of its crystal structure. In spite of the complexities, an entirely crystallographic procedure performed on a single grain can afford a practical way to identify and characterize these species; such a procedure is often successful, provided the quality of the cry stal allows it. We consider the crystal-chemical mechanisms corresponding to the most important substitutions, and apply such a method to identify the Fe-poor and Ca-rich gadolinite-group minerals from Cuasso al Monte, Varese, Italy. These crystals can be ascribed to hingganite-(Y), with minor amounts of gadolinite (0.26–0.31 molar fraction) and datolite components (0.15–0.25 molar fraction) in solid solution. The component minasgeraisite-(Y) is not present, even as a minor one, in the samples studied .
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".