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Record W2131734270 · doi:10.1144/0016-76492010-081

Geochemistry and U–Pb dating of felsic volcanic rocks in the Riotinto–Nerva unit, Iberian Pyrite Belt, Spain: crustal thinning, progressive crustal melting and massive sulphide genesis

2011· article· en· W2131734270 on OpenAlexaff
Alfonso Valenzuela, Teodosio Donaire Romero, Christian Pin, Manuel Toscano, Michael A. Hamilton, Emilio Soler Pascual

Bibliographic record

VenueJournal of the Geological Society · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFelsicGeologyPyriteGeochemistryVolcanic rockVolcanic beltVolcanoPetrology

Abstract

fetched live from OpenAlex

Abstract: We present new geochemical, Sm–Nd and U–Pb data on the felsic volcanic rocks containing the world-class volcanic-hosted massive sulphide deposits in the Riotinto–Nerva unit, Iberian Pyrite Belt, Spain. Three new U–Pb ages from older plagioclase–quartz-phyric dacites and plagioclase-phyric rhyolites to youngest plagioclase–quartz-phyric rhyolites indicate a time span for felsic volcanism ranging from 351.5 ± 0.4 to 345.7 ± 0.6 Ma. The youngest felsic rocks exhibit lower ε Nd , as well as contrasting Ti, Sr, Zr, Hf and Eu/Eu* values. We interpret that in the Riotinto–Nerva unit crustal melting successively affected shallower, more evolved horizons in the crust. Progressive crustal melting is consistent with current interpretations of the Iberian Pyrite Belt in terms of a late Devonian–Early Carboniferous transtensional setting, coupled with underplating by basic magma. We suggest that low ε Nd , evolved crustal magmatism could be used as a proxy in studies of the genesis of these and possibly other Phanerozoic massive sulphide deposits. Supplementary material: Details of the analytical methods and whole-rock data for basalts are available at http://www.geolsoc.org.uk/SUP18452 .

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)0.001
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.209
Teacher spread0.186 · 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

Citations46
Published2011
Admission routes1
Has abstractyes

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