Gorbunovite CsLi<sub>2</sub>(Ti,Fe<sup>+3</sup>)(Si<sub>4</sub>O<sub>10</sub>)(F,OH,O)<sub>2</sub> – a new mica supergroup mineral from the Darai-Pioz alkaline massif, Tajikistan
Bibliographic record
Abstract
Abstract Gorbunovite, CsLi 2 (Ti,Fe +3 )(Si 4 O 10 )(F,OH,O) 2 , a new caesium trioctahedral mica, was discovered in the Darai-Pioz alkaline massif, Tajikistan. The mineral is named after the Russian chemist, leader of the Tajik-Pamir Expedition, Academician Nikolai Petrovich Gorbunov (1892–1938). Gorbunovite occurs as lamellar grains or flakes from 2 μm to 0.2 mm in a quartz–pectolite aggregate and is associated with quartz, fluorite, pectolite, baratovite, aegirine, leucosphenite, neptunite, reedmergnerite, orlovite, sokolovaite, mendeleevite-(Ce), odigitriaite, pekovite, zeravshanite, kirchhoffite and garmite. The mineral is colourless, transparent, with vitreous lustre. Mohs hardness is 2½. D meas. is 3.28 (2), D calc is 3.302 g/cm 3 . Gorbunovite is optically biaxial (–), α = 1.609(2), β = 1.621(2), γ = 1.623(2), 2V meas. 30(5) and 2V calc. 44. Gorbunovite is monoclinic, space group C 2/ m, C 2 or Cm (polytype 1 M ), a = 5.236(2), b = 9.054(4), c = 10.767(4) Å, β = 99.61(4)°, V = 503.3(6) Å 3 and Z = 2. The strongest lines in the powder X-ray diffraction pattern [ d , Å, ( I )] are: 4.49 (25), 3.94 (20), 3.69 (46), 3.57 (23), 3.45(34), 2.991 (42), 2.608 (77), 2.581 (100), 2.240 (33), 2.188 (62), 2.020 (24), 1.722 (27) and 1.511 (23). Chemical composition (microprobe analysis; H 2 O, Li 2 O – SIMS) is: SiO 2 47.44, TiO 2 9.40, Al 2 O 3 0.66, MgO 0.63, Fe 2 O 3 3.64, ZnO 1.01, K 2 O 0.39, Cs 2 O 26.64, Li 2 O 5.83, H 2 O 0.89, F 4.48, –O=F 1.89, total 99.17. The empirical formula is (Cs 0.96 K 0.04 ) Σ1.00 Li 1.98 (Ti 0.60 Fe +3 0.23 Mg 0.08 Al 0.07 Zn 0.06 ) Σ1.04 Si 4.00 O 10 (F 1.19 OH 0.50 O 0.31 ) Σ2 .
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How this classification was reachedexpand
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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".