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Enregistrement W2981388381 · doi:10.5382/sp.15.1.10

The Discovery History and Geology of Corani<subtitle>A Significant New Ag-Pb-Zn Epithermal Deposit, Puno Department, Peru</subtitle>

2010· book-chapter· en· W2981388381 sur OpenAlexaboutno aff
Andrew Swarthout, Marc Leduc, C. Rios

Notice bibliographique

Revuenon disponible
Typebook-chapter
Langueen
DomaineComputer Science
ThématiqueGeochemistry and Geologic Mapping
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEconomic shortageNatural resource economicsConsumption (sociology)CommodityPrecious metalPaceService (business)BusinessCommerceAgricultural economicsEconomicsGeographyEconomyFinanceChemistryGovernment (linguistics)Sociology

Résumé

récupéré en direct d'OpenAlex

There seems to be general consensus throughout much of the global mining industry that the supply of base and precious metals and some other commodities (e.g., ferrous metals, uranium) is reasonably well assured into the oreseeable future because increases in total resources continue to keep pace with or outstrip global consumption. The basic assumption is that market forces and technological advances will combine to promote and perpetuate this trend (e.g., Tilton, 2003; Crowson, 2008). Others disagree, however, andpredict that shortages are inevitable if metal consumption continues to escalate (Beaty, 2010). It is already becoming clear that many known resources seem unlikely to be mined, irrespective of commodity prices, because of their low grade and/or quality. Hence, many mineral resources that were uneconomic in the early 2000s are likely to remain so, both today and into the foreseeable future because of increases in both the direct (e.g., energy, labor) and indirect (e.g., environmental, social) production costs. This situation is being further exacerbated by the perceived decrease, over at least the past decade, in the discovery rate of base and precious metal resources measured in terms of both the number of major discoveries made and the exploration dollars spent per discovery (e.g., Dummett, 2000; Horn, 2002; Schodde, 2004). There is also a suggestion that the discoveries made are, on average, becoming both smaller and lower grade. Therefore, it seems reasonable to ask whether current exploration practices and success rates are going to be adequate to provide for the massive increases in metal consumption that world population growth, rising living standards, and rapid industrialization and urbanization in China, India, and other emerging markets appear to portend. For example, Rio Tinto's projections suggest that "by 2030 the additional supplyrequired will be equivalent to replicating the iron ore output of the Pilbara region of Australia every five years, adding another aluminium production complex the size of Canada's Saguenay every nine months, and developing another copper mine the size of Escondida in Chile each year. Future energrequirements are such that an entire Hunter Valley coal supply chain needs to be created each year plus a uranium mine the size of Ranger every four years" (Albanese, 2010, p. 7). Clearly, the exploration business has to become increasingly effective if it is to rise to the challenge of finding mineral resources of the right caliber to assure that this burgeoning demand can be adequately satisfied. Corani is a significant recently discovered large silver and base metal deposit situated within the Corani mining district in the central Andes of Peru. The deposit is located 200 km northwest of the city of Puno, between 4,675 and 5,260 m in elevation, and includes 12 mineral claims covering an area of 5.7 km2. The silver, lead, and zinc resources represent low- to intermediate-sulfidation–style epithermal mineralization hosted within 23 Ma rhyolitic crystal lithic tuffs. Potentially economic epithermal gold mineralization also occurs within the district and requires further exploration. Previous district production includes small-scale underground antimony mining in the 1940s and selective mining from high-grade silver veins during the 1960s. During the 1990s, limited drilling focused upon an epithermal gold zone at the southern limits of the current Corani deposit. Rio Tinto staked the district in 2003 as a porphyry copper system. The presence of such a system remains a possible deep source for the recognized epithermal mineralization. Bear Creek Mining Corporation acquired the district from Rio Tinto in 2005 and drilled the first discovery holes in 2006. To date, more than 93,640 m of diamond drilling has been completed in conjunction with extensive studies in order to understand the controls of the base and precious metal mineralization. Mineralization occurs as stockwork veins, fracture coatings, and breccias localized within a westerly-dipping listric fault complex resulting from regional extension. These ore-hosting structures cut the rhyolitic tuffs of the Quenamari Formation. Dominant mineral phases include quartz, barite, pyrite, sphalerite, galena, hematite, and freibergite. The total mineable reserve is 139.6 million tons (Mt) averaging 57.5 g/t Ag, 0.94 percent Pb, and 0.46 percent Zn, thus containing 8.03 t Ag (258 million ounces (Moz)), 1.31 t Pb (2.9 billion lbs.), and 0.65 t Zn (1.4 billion lbs.) recovered into concentrates. In addition, 145 Mt of lower grade material is maintained in resources. An understanding of the distribution of mineralization styles, defined by using metallurgical testing, mineragraphic analysis, and detailed core logging, is critical in unlocking the economic potential of the deposit and developing a three-dimensional model for mining. Of particular importance to future development is the overprinting by supergene mineral assemblages, including complex lead and/or barium phosphates and iron and/or manganese oxides.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,030
Score d'incertitude au seuil0,059

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0030,003
Études des sciences et des technologies0,0030,003
Communication savante0,0020,002
Science ouverte0,0010,003
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0090,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,014
Tête enseignante GPT0,187
Écart entre enseignants0,174 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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