MINERALOGY OF THE NIEDERSCHLEMA ALBERODA U Se POLYMETALLIC DEPOSIT, ERZGEBIRGE, GERMANY. I. JOLLIFFEITE, NiAsSe, THE RARE Se-DOMINANT ANALOGUE OF GERSDORFFITE
Bibliographic record
Abstract
The Niederschlema-Alberoda uranium deposit, in the Erzgebirge region of Germany, contains an uncommon assemblage of metallic minerals, in particular selenides, sulfides, arsenides, tellurides, and native elements, in addition to uraninite and coffinite. The complex mineralogy resulted from the superposition of several mineralizing events over the time interval from the Permian to the Cretaceous; these events introduced and redeposited a great variety of metallic elements within the hydrothermal uranium deposit (Pb, Ag, Cu, Hg, Tl, Bi, Co, Ni, As, Sb, Se, S, Te). One of the exotic minerals is jolliffeite, an arsenoselenide with end-member composition NiAsSe, so far only known from Lake Athabasca, Saskatchewan, Canada. A single, small, anhedral grain of jolliffeite from Niederschlema-Alberoda is included and partly replaced by sulfurian eskebornite. Associated minerals comprise hematite, Ni-Co-Se-bearing lollingite, clausthalite, tiemannite, mercurian hakite-giraudite solid solutions, sulfurian berzelianite, sulfurian umangite, hessite, Ni-Co-As-bearing pyrite, and Se-rich chalcopyrite. The sulfurian jolliffeite has the empirical formula (Ni0.85Cu0.09Co0.05Fe0.02Ag0.01)Sigma(1.02)As(0.98)(Se0.77S0.23)(Sigma1. 00) and differs from type jolliffeite mainly by substantial substitution of Cu (2.6-3.3 wt.%) for Ni and S (3.2-4.1 wt.%) for Se. Substantial S-for-Se substitution in jolliffeite implies extensive and probably complete miscibility between NiAsSe and its S-dominant analogue, gersdorffite-Pa3 (NiAsS). We suggest that a localized accumulation of Ni and As in the Se-(S)-bearing hydrothermal fluid gave rise to the crystallization of jolliffeite at some rare locations at a late stage of formation of the Jurassic selenide assemblage
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".