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Origin of potassium-bearing tourmalines of the Kumdy-Kolsky deposit (Kokchetav massif, Northern Kazakhstan): Study of Mineral inclusions

2023· article· en· W4386542104 on OpenAlexaff
Andrey V. Korsakov, Kira Musiyachenko, Д. С. Михайленко, Sergey P. Demin

Bibliographic record

VenueLITHOSPHERE (Russia) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTourmalinePotassiumGeologyMineralogyMineralZirconMassifGeochemistryChemical compositionInclusion (mineral)Analytical Chemistry (journal)ChemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

Research subject . Mineral inclusions in potassium-bearing tourmaline crystals of the Kumdy-Kol microdiamond deposit. Aim . To reconstruct PT conditions for the origin of potassium-bearing tourmalines. Materials and methods . Mineral analysis and element mapping were performed using an X-ray spectral microanalyzer. Raman spectroscopy was used to detect the C and SiO 2 polymorphs. Results . For the first time, diamond inclusions were identified in tourmalines with the potassium content ranging from 1.0 to 1.6 wt %. In addition, diamond-bearing zircon was detected in tourmaline crystals, with the K 2 O content below the detection limit. Previously, diamond inclusions had been exclusively identified only within the most potassium-rich cores of tourmaline crystals, which were approved as a new end member referred to as maruyamaite. Similar to the previous studies, the Kfs inclusions were recognized in both marumaite crystals and tourmaline crystals, with a variable content of potassium. Conclusions . The obtained findings indicate that high-pressure conditions may not be necessary for the formation of potassium-rich tourmaline. The chemical composition of the fluid is most likely to be the main factor controlling the appearance of tourmalines with an unusual composition.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.226
Teacher spread0.207 · 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.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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