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Record W4410317135 · doi:10.3390/min15050511

Barian Micas and Exotic Ba-Cr and Ba-V Micas Associated with Metamorphosed Sedimentary Exhalative Baryte Deposits near Aberfeldy, Scotland, UK

2025· article· en· W4410317135 on OpenAlexaboutno aff
Norman Moles

Bibliographic record

VenueMinerals · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
FundersDepartment of Education and Learning, Northern Ireland
KeywordsGeochemistrySedimentary rockGeologyIgneous rock

Abstract

fetched live from OpenAlex

Regionally metamorphosed, Neoproterozoic stratiform baryte deposits near Aberfeldy in the Grampian Highlands of Scotland, UK, contain barium-poor and barium-rich micas in the host rocks and mineralized strata, respectively. The barium-rich micas include muscovite, biotite, phlogopite, and chromium-bearing muscovite. They occur in schistose metasediments and metabasites, in barium-feldspar rocks, and in small amounts in baryte rock. An extensive study of micas in a range of lithologies using electron-probe micro-analysis found up to 10.86 wt% BaO in muscovite, 5.46 wt% in biotite, and 15.70 wt% in Ba-Cr muscovite, the latter containing up to 9.27 wt% Cr2O3. Compositions are comparable with Ba- and Ba-Cr-micas in other metamorphosed Sedimentary Exhalative deposits and barium-rich metasediments worldwide. In one baryte rock sample, disseminated crystals of an exotic Ba-V-Cr mica contain up to 12.33 wt% BaO and 10.82 wt% V2O3, compositionally similar to Ba-V micas in the Hemlo lode gold deposit, Ontario. Ba2+ incorporation is mainly by coupled substitution with Al3+ for K+ + Si4+ in the tetrahedral site. The extent of phengitic (Tschermakitic) substitution is typical of micas in amphibolite-facies metasediments. Similar Fe:Mg ratios in coexisting muscovite and biotite reflect partitioning of iron into sulphides and metamorphic equilibration, with rare exceptions in fine-grained rocks that exhibit millimetre-scale disequilibrium.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.210
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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