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Record W2051802383 · doi:10.2113/econgeo.109.8.2227

Episodic Subseafloor Hydrothermal Activity Within the Eastern Manus Back-Arc Basin Determined by Uranium-Series Disequilibrium in Barite

2014· article· en· W2051802383 on OpenAlexaboutno aff
Susan Johns, R. G. Ditchburn, B. Barry, C.J. Yeats

Bibliographic record

VenueEconomic Geology · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
FundersCommonwealth Scientific and Industrial Research Organisation
KeywordsResource (disambiguation)UraniumManusEarth scienceGeologyLibrary scienceOceanographyGeochemistryGeographyPaleontologyComputer science

Abstract

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Research Article| December 01, 2014 Episodic Subseafloor Hydrothermal Activity Within the Eastern Manus Back-Arc Basin Determined by Uranium-Series Disequilibrium in Barite Shannon M. Johns; Shannon M. Johns † 1CSIRO Earth Science and Resource Engineering, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, Western Australia 6151, Australia †Corresponding author: e-mail, shannon.heggie@ontario.ca Search for other works by this author on: GSW Google Scholar Robert G. Ditchburn; Robert G. Ditchburn 2Cosmogenic Isotope and Radiochemistry Laboratory, GNS Science, National Isotope Centre, 30 Gracefield Road, Gracefield, Lower Hutt 5010, New Zealand Search for other works by this author on: GSW Google Scholar Bernard J. Barry; Bernard J. Barry 2Cosmogenic Isotope and Radiochemistry Laboratory, GNS Science, National Isotope Centre, 30 Gracefield Road, Gracefield, Lower Hutt 5010, New Zealand Search for other works by this author on: GSW Google Scholar Christopher J. Yeats Christopher J. Yeats 1CSIRO Earth Science and Resource Engineering, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, Western Australia 6151, Australia Search for other works by this author on: GSW Google Scholar Author and Article Information Shannon M. Johns † 1CSIRO Earth Science and Resource Engineering, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, Western Australia 6151, Australia Robert G. Ditchburn 2Cosmogenic Isotope and Radiochemistry Laboratory, GNS Science, National Isotope Centre, 30 Gracefield Road, Gracefield, Lower Hutt 5010, New Zealand Bernard J. Barry 2Cosmogenic Isotope and Radiochemistry Laboratory, GNS Science, National Isotope Centre, 30 Gracefield Road, Gracefield, Lower Hutt 5010, New Zealand Christopher J. Yeats 1CSIRO Earth Science and Resource Engineering, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, Western Australia 6151, Australia †Corresponding author: e-mail, shannon.heggie@ontario.ca Publisher: Society of Economic Geologists First Online: 09 Mar 2017 Online ISSN: 1554-0774 Print ISSN: 0361-0128 © 2014 Society of Economic Geologists. Economic Geology (2014) 109 (8): 2227–2242. https://doi.org/10.2113/econgeo.109.8.2227 Article history First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Shannon M. Johns, Robert G. Ditchburn, Bernard J. Barry, Christopher J. Yeats; Episodic Subseafloor Hydrothermal Activity Within the Eastern Manus Back-Arc Basin Determined by Uranium-Series Disequilibrium in Barite. Economic Geology 2014;; 109 (8): 2227–2242. doi: https://doi.org/10.2113/econgeo.109.8.2227 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEconomic Geology Search Advanced Search Abstract The geochronology of seafloor hydrothermal activity from several mineralized, active and inactive vent fields at Suzette and Pual Ridge, eastern Manus back-arc basin, Bismarck Sea, Papua New Guinea, has been established using the 228Th/228Ra, 228Ra/226Ra, and 226Ra/Ba uranium-series disequilibrium methods for barite-rich samples. These hydrothermal systems underwent episodes of hydrothermal fluid circulation that produced barite over the last ~6,000 years. Precipitation of hydrothermal barite, disseminated within the host rock and lining fractures, vugs, and conduits, was controlled by decreasing temperatures and mixing of hydrothermal fluids with oxidized seawater. Repeated fluctuations in hydrothermal fluid temperature and chemistry resulted in complex sequences of barite and sulfide minerals lining vugs and conduits, whereas rapid cooling following fracture events led to precipitation of only barite and some Fe oxide coatings on barite crystals. A wide range in ages of barite within drill cores (i.e., 380–5,990 yrs before present (BP)) reflect repeated pulses of hydrothermal fluids through the altered volcanic and mineralized rocks that make up the hydrothermal mound structures, with the younger ages (i.e., 34–220 yrs BP), representing more recent barite-precipitating fluid circulation accessing fractures, veins, and vugs. Barite from chimney samples is mostly young (i.e., 23–1,680 yrs BP), with the majority precipitated between 23 to 41 yrs BP; reflecting the structural stability (standing life) of the chimneys and possible influences from varying hydrothermal fluid chemistry or reactivation of vent fields. Three generalized age groupings, representing major episodes of barite-precipitating hydrothermal fluid circulation, are resolved from the Suzette area (19–45, 810–1,900, and 3,740–4,710 yrs BP, including 1σ errors); with the most recent ages recorded from both the Suzette and Pual Ridge areas. Fast-spreading rates within the Manus basin, an abundance of faults and variable magmatic inputs are major factors controlling the frequency and longevity of these episodes of hydrothermal activity. Mineral resource models and comparisons indicate that the Cu-Zn-Ag-Au–rich Suzette deposit is small; however the measured age range is comparable to ages given for modeled (typical) seafloor massive sulfide deposits from back-arc and arc environments. We suggest that the scale of the Suzette deposit may have been limited during formation by a low hydrothermal fluid flux and/or inappropriate physical and chemical conditions for sufficient metal precipitation from hydrothermal fluids. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.003

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 head0.008
GPT teacher head0.177
Teacher spread0.169 · 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; both teacher heads agree on what is shown here.

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".

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Citations9
Published2014
Admission routes1
Has abstractyes

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