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Record W3034832557 · doi:10.3749/canmin.1900055

Mineral chemistry and geochronology of the Rajasthan emerald deposits, NW India

2020· article· en· W3034832557 on OpenAlexaffvenue
Paul Alexandre

Bibliographic record

VenueThe Canadian Mineralogist · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsBrandon University
Fundersnot available
KeywordsPhlogopiteMuscoviteGeologyPegmatiteGeochemistryTourmalineSchistBiotiteOrogenyGneissMetasomatismSphaleriteGeochronologyMineralMetamorphic rockQuartzPyriteMantle (geology)ChemistryGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

ABSTRACT The emerald deposits in Rajasthan, northwest India, are situated in a narrow NE–SW belt in the Aravalli Mountains. The studied deposits were formed by the metasomatic reaction between muscovite (± garnet ± tourmaline) pegmatites and lenticular bodies of altered ultramafic rocks that are hosted by the Delhi Group gneisses. This reaction produced phlogopite schists containing the exometasomatic emeralds, as in all other granite-related emerald deposits. Endometasomatic changes of the mineralogy of the pegmatites is indicated by the geochemistry of the muscovite (phengitic substitution) and the feldspars (disappearance of the potassic feldspar and calcification of the plagioclase). The K-Ar analyses of syngenetic phlogopite (from the phlogopite schist) and muscovite (from the pegmatites) give an age of ca. 790 Ma, close to that of the last major orogeny affecting the region. This is in accordance with the ages of other granite-related deposits, which all formed in conditions of active orogeny. The ages of the biotite are lower than those of the muscovite, indicating limited radiogenic argon loss as a result of deformation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.167
Teacher spread0.156 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2020
Admission routes2
Has abstractyes

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