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Record W2065814966 · doi:10.3749/canmin.46.4.807

THE ARSHAN REE CARBONATITES, SOUTHWESTERN TRANSBAIKALIA, RUSSIA: MINERALOGY, PARAGENESIS AND EVOLUTION

2008· article· en· W2065814966 on OpenAlexvenueno aff
А. G. Doroshkevich, G. S. Ripp, Shrinivas G. Viladkar, N. V. Vladykin

Bibliographic record

VenueThe Canadian Mineralogist · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsParagenesisCarbonatiteGeologyGeochemistryMineralogyMetamorphic rock

Abstract

fetched live from OpenAlex

The Arshan carbonatites in the Transbaikalia region of Siberia consist of sovite with high concentrations of the REE, Sr, Ba, and SO 3 , and low concentrations of Nb and P 2 O 5 . There was a high fugacity of oxygen and fluid activity at the time of formation of these carbonatites, and they were later altered by hydrothermal solutions. Bastnasite formed as a magmatic mineral in the carbonatites, on the basis of petrographic evidence and fluid-inclusion data. The recrystallization of calcite, the replacement of bastnasite and phlogopite, and the formation of secondary sulfates, strontianite, calcite and fluorite resulted from a hydrothermal process. The 87 Sr/ 86 Sr values of minerals in the Arshan carbonatites are higher than in many other carbonatites, but are similar to those in the continental basalts of Transbaikalia. The δ 34 S CDT values resemble those of other Transbaikalia carbonatites and alkaline rocks. The δ 13 C V–PDB isotopic values in the carbonatite plot within the field defined for primary igneous carbonatites. On the other hand, δ 18 O V–SMOW values for the Arshan bastnasite is only partially within the usual range of mantle values. The altered carbonatites are characterized by lighter δ 18 O values, probably because of the influence of meteoric water. The carbonatites were formed from an enriched source in the mantle and crystallized rapidly at shallow depth.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.915

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 studies0.0010.001
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 head0.017
GPT teacher head0.175
Teacher spread0.159 · 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

Citations38
Published2008
Admission routes1
Has abstractyes

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