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Record W1965885257 · doi:10.4043/19849-ms

SS: Ocean Mining: The Science Of Seafloor Massive Sulfides (SMS) In The Modern Ocean - A New Global Resource For Base And Precious Metals

2009· article· en· W1965885257 on OpenAlexaff
Yves Fouquet, S. D. Scott

Bibliographic record

VenueOffshore Technology Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeologyGeochemistrySeafloor spreadingBasaltLavaOceanic crustUltramafic rockPillow lavaMid-ocean ridgeHydrothermal circulationVolcanogenic massive sulfide ore depositIsland arcFelsicVolcanoSubductionGeophysicsPyritePaleontologyTectonics

Abstract

fetched live from OpenAlex

Abstract High temperature hydrothermal activity was first observed 30 years ago in the modern oceans where hot springs are precipitating sulfide-sulfate-silica mounds and columnar edifices (" chimneys??) of calcium, barium, iron, copper, zinc, lead, silver and gold with other minor elements. Hydrothermal fields are now known in several major geodynamic settings (slow and fast spreading ridges, back-arc basins, arcs, and fore arcs) and associated with various types of basement rocks (basalt, andesite and dacite volcanic; sediment; and ultramafic intrusions from the mantle). According to their geodynamic setting and the composition of the basement rocks, hydrothermal sulfide deposits can be divided in five major types:Mid ocean ridges + basalt = oceanic crust type;Slow spreading ridges + ultramafic rocks = mantle type;Arc or immature back-arc + felsic lava = Back-arc type); Mid-ocean ridge + sediments + basalt = sedimented ridge type; and Back-arc + continental sediments + felsic lava = sedimented back arc type. Active sites are known at water depths from a few hundreds of meters to 4100 m. The mineral and chemical compositions of sulfides are strongly dependent on the basement rock composition, the degree of maturation of the deposit, the geodynamic setting and, in some cases, on the input of magmatic fluids. At another scale, the composition of fluids and sulfide mineralization is controlled by various physical and chemical processes. One important process, related to pressure and water depth, is phase separation. Modern hydrothermal fields provide insight into geological controls, as well as the mode of formation of Submarine Massive Sulfide (SMS) deposits. On fast spreading ridges, the discharge is unstable and the style of activity varies according to the relative importance of tectonic and volcanic activities. Axial hydrothermal fields are small; however, large sulfide deposits can be formed on off-axial volcanoes. On slow spreading ridges, the hydrothermal activity is more stable and better focused. Hydrothermal fields are much larger than on fast spreading ridges but the spacing between fields is greater. Geological controls are variable: the top of the axial volcanoes where the control is volcanic is one control, but also the base and the top of the rift valley walls, as well as non-transform discontinuities where the control is tectonic and basement rocks often dominated by ultramafic rocks. Back-arc hydrothermal fields also vary depending on the importance of tectonic versus volcanic activity. The style of the discharge and the morphology of mineralization are influenced by the strong permeability of the felsic, vesicular and brecciated lava. Discharge occurs often as extensive (>1km) low temperature deposits at the top of the volcaniclastic ridges. The first observations of black smokers led to the understanding that the SMS deposits were formed primarily by accumulations of chimneys on the oceanic floor. The most recent investigations, and in particular operations of the Ocean Drilling Program showed that they are formed by three principal processes:Accumulations of chimneys on the seafloor;sulfate and sulfide precipitates within the mound; andReplacement of basement rocks (volcanic, ultramafic rocks or sediments). The morphology of mineralization is controlled by the permeability of basement rocks. In the more mature mounds, zone refining processes produces a mineral and chemical zonation of the sulfide mounds.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.248
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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