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Record W2580829120 · doi:10.17491/jgsi/2006/670408

Geochemical Study of Shaxi Porphyry Copper-Gold Deposit in Southern Part of Tan-Lu Fault Belt, East China

2006· article· en· W2580829120 on OpenAlexaff
Xiaoyong Yang, Kuiren Wang

Bibliographic record

VenueJournal of the Geological Society of India · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGeologyGeochemistryClastic rockVolcanic rockFaciesFault (geology)Mineralization (soil science)DevonianVolcanoGeomorphologySedimentary rockPaleontologyStructural basin

Abstract

fetched live from OpenAlex

Abstract Shaxi porphyry Cu-Au deposit in central Anhui Province is located in the Middle-Lower reaches of Yangtze metallogenic valley in east China Red sandstone and conglomerate of Cretaceous age, clastic rocks of Middle and Lower Jurassic, clastic rocks of continental sea facies of Upper Devonian-Middle Silurian age, various continental volcanic rocks of Jurassic age form the rock types of the Shaxi porphyry copper-gold metallogenic belt The ore district is cut by multiple faults, of which the most important are Tanlu fault and Fanshan-Tongling faults, the former being the largest fault system in East Asian continent and the later being the regional deep fault The geological, geochemical and mineralogical methods used to investigate the porphyry copper-gold deposit associated with large scale sulphide mineralization forms the theme of this paper Through field geological surveys, mineralogical observation, compositional analyses on minerals using EMPA, geochemical analyses on Cu-Au-bearing intrusive rocks, fluid inclusion and oxygen, hydrogen, sulphur isotopic studies, and element distributions detected by PIXE system, the characteristics of mineralization and gold occurrence in the Shaxi porphyry copper-gold deposit have been fully investigated The results of the study form the basis for further research and exploration on the porphyry copper-gold deposit of the Middle-Lower Yangtze region

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)0.001
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 score0.016
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.220
Teacher spread0.201 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

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