Bibliographic record
Abstract
This New Mineral Names has entries for 10 new minerals, including bulgakite, dyrnaesite-(La), eleonorite, gatewayite, joanneumite, mendeleevite-(Nd), morrisonite, nolzeite, packratite, vanarsite and a new data on nalivkinite. # Bulgakite* and New Data on Nalivkinite {#article-title-2} A.A. Agakhanov, L.A. Pautov, E. Sokolova, Y.A. Abdu and V.Y. Karpenko (2016) Two astrophyllite-supergroup minerals: bulgakite, a new mineral from the Darai-Pioz alkaline massif, Tajikistan and revision of the crystal structure and chemical formula of nalivkinite. Canadian Mineralogist, 54(1), 33–48. Bulgakite, (IMA 2014-041), ideally ![Formula][1] , is a new astrophyllite-supergroup mineral. It occurs in the moraine of the Darai-Pioz glacier (39°30′N 70°40′E) in the upper Darai-Pioz alkaline massif in the upper reaches of the Darai-Pioz river, in the area of the joint Turkestan, Zeravshan, and Alay Ranges, Tajikistan. The Darai-Pioz massif is a multiphase intrusion and occupies the core of a large synclinal fold of Carboniferous (Pennsylvanian series) slates. Rocks of the massif have been intruded by fine-grained dikes of biotite tourmaline granites and veins of calcite carbonatites and fenites. Bulgakite was found in a naturally tumbled amphibole–quartz–feldspar boulder of spotty texture, as individual crystals and intergrowths in small cavities (up to 0.5 cm) and as intergrowths (up to 1 cm) of platy crystals and aggregates of poorly crystallized grains. Associated minerals are alkali amphibole, quartz, microcline, bafertisite, aegirine, calcybeborosilite-(Y) , thorite, fluorite, and later crystallized brannockite and sogdianite. Bulgakite is brownish orange with a pale brown streak and a vitreous luster. Cleavage is perfect parallel to {001} and moderate parallel to {010}. The indentation hardness of bulgakite is VHN50 = … [1]: /embed/mml-math-1.gif
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.251 | 0.219 |
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".