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Record W4416282803 · doi:10.17491/jgsi/2008/720309

Paleoproterozoic Boninite-Iike Rocks in an Intracratonic Setting from Northern Bastar Craton, Central India

2008· article· en· W4416282803 on OpenAlexaboutno aff
D. V. Subba Rao, V. Balaram, K. Naga Raju, D. N. Sridhar

Bibliographic record

VenueJournal of the Geological Society of India · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMaficCratonArcheanMagmatismLilePlagioclasePartial meltingMetasomatism

Abstract

fetched live from OpenAlex

Abstract: Boninite-like rocks represented by high-Ca boninitic dykes, melanogabbro dykes, recrystallized plagioclase bearing high MgO dykes and high-Mg norite suites occur at few places in the vicinity of Meso to Neoproterozoic Chhattisgarh sedimentary basin in the northern Bastar craton in Central India These rocks are formed in an intracratonic setting, not at convergent margin, similar to Archaean boninitic rocks reported from intracratonic settings such as Mallina Basin, Northwest Australia and Abitibi, Optica regions of Canada These high-MgO mafic dykes show a strong boninitic affinity with high SiO2 (>52%), high MgO (9-15%), low TiO2 (0.30-0.54 wt%) and strong LILE enrichment These unusual dykes show distinct mineralogical, petrological and geochemical characteristics and are totally different to that of the normally occurring abundant metadoleritic and metagabbroic dykes in Chhattisgarh region The generation of boninite magmatism requires unique thermal conditions such as shallow melting, elevated geothermal gradient and subducted slab flux On the basis of field, geological, petrological and geochemical inferences on these Chhattisgarh boninitic and noritic dykes, a two-stage melting model and derivation from a strongly depleted mantle source, ennched later by metasomatic events is suggested

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 score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.010
GPT teacher head0.188
Teacher spread0.178 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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