Notice bibliographique
Résumé
Abstract This paper reviews and analyzes the role played by changes in mineral exploration practice on the discovery record worldwide, over a timeframe of roughly the last 50 years. Geologic field methods have remained relatively unchanged, although general geologic theory as well as some empirical and genetic ore deposit models and related concepts have undergone major revisions that have had significant but unquantifiable effects on the exploration process. The principal geochemical and geophysical methods employed in the 1950s and 1960s remain preeminent, notwithstanding the burgeoning sophistication of analytical techniques and geophysical instrumentation, and the exponential increases in data-processing capacity. Remote sensing and data management and modeling technology have also both advanced apace over the last two decades. The evolution of these earth-science disciplines affected the practicalities of mineral exploration in various ways, as demonstrated using porphyry Cu, volcanogenic massive sulfide (VMS), sediment-hosted (Carlin-type) Au, epithermal Au, orogenic (mesothermal) lode Au, and magmatic Ni-Cu deposits as examples, although constancy in search procedures prevailed over radical change. Advances in the geologic, geochemical, geophysical, and remote-sensing fields do not seem to have greatly influenced the discovery record, at least where the most reliable compilations are available, for the circum-Pacific region over the last 35 years. Discovery has resulted mainly from routine fieldwork complemented by conventional geochemistry, and to a far lesser degree, from ground geophysics. Nevertheless, geophysics has made a greater contribution to discovery of the increasing number of deposits concealed beneath pre- and postmineralization cover. In Precambrian shield areas, such as Canada, Australia, and Scandinavia, with a dominance of different ore deposit types and distinct physiographic conditions, airborne geophysics has clearly played a more influential role in discovery, particularly of VMS, magmatic Ni-Cu, unconformity related U, and diamond deposits as well as greatly contributing to regional geologic understanding. Perpetuation of broadly the same exploration approach, using tried-and-tested field-based methods, is strongly advocated, especially in the case of green-field programs. Continued innovative exploration of the world’s premier metallogenic belts and provinces must be combined with search for new, highly endowed frontier regions. While geologic and geochemical modeling remains vital for brown-field exploration, a greater future role for geophysics and grid and fence drilling is envisioned. Technologic advances in all these fields will undoubtedly facilitate an increasing number of exploration tasks, particularly data gathering, handling, and analysis, but are thought unlikely to dramatically change the discovery process and could even have a negative influence if not used to enhance productive field time. Future exploration success, especially under deep cover, demands more predictive ore deposit models and geochemical and geophysical methods that are better able to penetrate the overburden. The overall quality and inventiveness of exploration programs must improve, however, if the perceived decline in discovery rate and rise in discovery cost are to be remedied. Carefully targeted research on all fronts is necessary and should be welcomed.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,002 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».