Origin of potassium-bearing tourmalines of the Kumdy-Kolsky deposit (Kokchetav massif, Northern Kazakhstan): Study of Mineral inclusions
Bibliographic record
Abstract
Research subject. Mineral inclusions in potassium-bearing tourmaline crystals of the Kumdy-Kol microdiamond deposit. Aim. To reconstruct PT conditions for the origin of potassium-bearing tourmalines. Materials and methods. Mineral analysis and element mapping were performed using an X-ray spectral microanalyzer. Raman spectroscopy was used to detect the C and SiO2 polymorphs. Results. For the first time, diamond inclusions were identified in tourmalines with the potassium content ranging from 1.0 to 1.6 wt %. In addition, diamond-bearing zircon was detected in tourmaline crystals, with the K2O content below the detection limit. Previously, diamond inclusions had been exclusively identified only within the most potassium-rich cores of tourmaline crystals, which were approved as a new end member referred to as maruyamaite. Similar to the previous studies, the Kfs inclusions were recognized in both marumaite crystals and tourmaline crystals, with a variable content of potassium. Conclusions. The obtained findings indicate that high-pressure conditions may not be necessary for the formation of potassium-rich tourmaline. The chemical composition of the fluid is most likely to be the main factor controlling the appearance of tourmalines with an unusual composition.
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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) | 0.001 | 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".