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Record W2980985329 · doi:10.5382/av100.26

Andean Copper Province<subtitle>Tectonomagmatic Settings, Deposit Types, Metallogeny, Exploration, and Discovery</subtitle>

2005· book-chapter· en· W2980985329 on OpenAlexaboutno aff
Richard H. Sillitoe, José Perelló

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsSubtitleMetallogenyGeologyPolitical scienceLibrary scienceGeochemistryPhilosophy

Abstract

fetched live from OpenAlex

Abstract The Andes, in particular their central parts, have been known as a preeminent Cu province for more than 100 years and have been the source of many innovative metallogenic concepts and models directly applicable to Cu deposits worldwide. The central Andes currently produce 44 percent of world-mined Cu. The ~6,000-km-long Andean Cu province comprises several long and markedly linear, orogen-parallel metallogenic belts, each developed during a restricted metallogenic epoch. Belts in the northern Andes are still poorly explored, those in the central Andes are the focus of current Cu exploration and mining, and the southern Andes have little Cu potential. In the central Andes, from southern Peru to central Chile and contiguous Argentina, an incipiently developed belt of late Paleozoic to early Mesozoic porphyry Cu mineralization is partly overlapped by four eastward-younging Cu belts: middle to late Mesozoic on the Pacific coast, Paleocene to early Eocene, middle Eocene to early Oligocene, and, along the eastern border of the orogen, Miocene to early Pliocene, all but the first dominated by porphyry Cu mineralization. Porphyry Cu deposits in the northern part of the Paleocene to early Eocene belt, in southern Peru, and the southern part of the premier middle Eocene to early Oligocene belt, in northern Chile, coincide with major orogen-parallel fault systems that underwent synmineralization reverse displacement. The middle to late Mesozoic belt also contains major orogen-parallel faults but with normal and normal-oblique motions synchronous with Cu mineralization of Fe oxide-Cu-Au, manto-type Cu, and subordinate porphyry Cu types. In contrast, remaining portions of the Tertiary Cu belts, along with the central Chile segment of the Miocene to early Pliocene belt, lack evidence for such clearcut structural control on deposit location. The spatial distribution of Cu belts farther north is different, with only the Miocene to early Pliocene belt recognized in the central Andes of northern Peru and at least three belts developed semicontinuously in the northern Andes of Ecuador and Colombia. Compositions of host porphyry stocks and alteration-mineralization types and geometries in porphyry Cu-Mo and Cu-Au deposits throughout the Andes are grossly similar to those encountered elsewhere and do not appear to control either deposit size or hypogene ore grade. Nevertheless, deposits in the middle Eocene to early Oligocene belt of northern Chile, in particular, are characterized by telescoping of structurally localized high-sulfidation mineral assemblages over earlier and deeper alteration types. Hydrothermal breccias occur in many porphyry Cu centers, but ore-bearing varieties are volumetrically important in only three widely scattered deposits of different ages. Porphyry Cu-Au deposits and prospects, although concentrated in several discrete sub-belts and districts, also occur randomly throughout most of the belts. Geochronologic studies of several major deposits suggest that magmatic-hydrothermal lifespans commonly approximate 1 to 2 m.y. The three most productive porphyry Cu belts developed syntectonically during contractional events and crustal thickening, possibly linked to shallow subduction, forearc subduction erosion, and consequent arc migration. Suppression of volcanism during compression, high surface uplift rates, and rapid exhumation optimized the conditions for accumulation of fluid-rich magma in large, shallow-level chambers propitious for giant porphyry Cu development. The uplift was also ultimately responsible for the supergene upgrading of many Cu deposits, particularly in northern Chile. The concept of giant porphyry Cu deposit formation by superposition of two temporally discrete magmatic-hydrothermal systems lacks geologic support. Crustal composition appears to have exerted little influence on porphyry Cu genesis. In marked contrast to these contractional settings, extensional arcs in the Meso-Cenozoic Andes gave rise to smaller, lower grade porphyry Cu deposits. The attenuated crust, high heat-flow regime, and abundance of basaltic to intermediate-composition magmatism, characteristic of the middle to late Mesozoic belt in coastal southern Peru and Chile, provided optimal conditions for Fe oxide-Cu-Au and manto-type Cu formation, although the role of magmatic versus basinal brines in deposit genesis remains unresolved. A variety of geologic, geochemical, and geophysical techniques have been employed in Andean Cu exploration, but it is the combined routine geologic-geochemical approach that has resulted in most discoveries, including those during the past few years. Continued reliance on these tried-and-tested techniques, combined with timely drilling, is likely to be the best means of ensuring future exploration success. During the last 13 years, more than half of discoveries in the central Andes have been made beneath pre- or postmineral cover, a trend that is thought likely to continue. Nevertheless, undiscovered, at least partially exposed mineralization is also considered to exist, even in the premier middle Eocene to early Oligocene belt, which has accounted for approximately 65 percent of all Andean discoveries over the last three decades. Conceptual geology capable of predicting deposit locations, has played a very subordinate role in Cu discovery to date but is believed to be perhaps the single most underappreciated parameter for increasing the future discovery rate.

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.175
Threshold uncertainty score0.464

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1390.029

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 head0.013
GPT teacher head0.196
Teacher spread0.182 · 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".

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Citations150
Published2005
Admission routes1
Has abstractyes

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