Mobile metal ionization: effectiveness in gold exploration

Thesis (M.S.) University of Alaska Fairbanks, 2016A series of investigations and tests vetting the proprietary Mobile Metal Ion™ (MMI) technique for its effectiveness specifically in regards to identify Au concentrations in the subsurface. The Marigold Mine, north central NV, and the Gil Prospect, Interior AK, near Fairbanks, provide two site areas under active exploration and development in drastically contrasting environments. MMI has been widely available as an alternative to conventional soil geochemical methods since the 1990's, during which time it has been used successfully to identify several base metal deposits, mostly in arid climates. Criticisms and reluctance from industry to use the method generally stem from the poor understanding of ion migration mechanisms in the subsurface, and the proprietary extractants' undisclosed composition. While MMI has shown promise in the identification of large base metal deposits, Au is significantly less mobile than other metals at the near surface; a detailed investigation of MMI's ability to identify buried Au deposits is yet to be documented. This thesis conducts a critical review of MMI's overall effectiveness at identifying Au in the subsurface through a combination of small studies investigating both its analytical and geological reproducibility, and comparisons of soil anomalies to subsurface Au identified through drilling. Marigold areas tested with MMI (2007-2009, 2012) are currently being mined, allowing best-case scenario comparisons between ore grade and surface response; whereas at Gil investigations compare MMI responses to total organic carbon (TOC) profiles in soil cores, and test the method's usefulness in variably permafrost-rich soils. Both sites provide comparisons to conventional methods illustrating: MMI's advantages over conventional techniques in situations with between 5 to 100 meters alluvial cover; an interesting case where both MMI and conventional methods identified different portions of a deposit but neither method successfully defined it in its entirety; and strange inter-elemental correlations in the MMI data that appear to be reflecting how metals concentrate in the soils rather than reflecting bedrock metal correlations. Data also identify how some metals (e.g. As, Bi, Co, Fe, and Zn) preferentially concentrate in the A horizon soils, whereas others such as Au and Ba concentrate in the B horizon. Such results question our generally accepted models of how metals concentrate in soils. The A horizon (commonly considered the zone of leaching) is thought to have lower metal concentrations than the B horizon (zone of accumulation). However if these data are representative, then certain elements preferentially concentrate in the A horizon. Such knowledge will have serious implications on sampling protocols and interpretation of geochemical soil surveys in general.Chapter 1:Introduction -- Chapter 2: Geochemistry of the Marigold Deposit Mineralization -- Chapter 3: Mobile Metal Ion Investigations of the Marigold Deposit -- Chapter 4: Geochemical Investigations of the Gil Prospect, Alaska -- Chapter 5: Discussion and Conclusions -- References -- Appendices

Practice, Community, and Algorithms: How YouTube Creators Learn Through Making

In this thesis, I answer the following questions: How do YouTube content creators learncontent creation through their practice and participation in communities of practice? How do these communities help creators form identity? And, lastly, how do the YouTube’s automated systems shape creators’ practice and impact their identity? To explore these questions, I observed a community of new creators to understand how creators learned about content creation from others. I interviewed 11 YouTube creators that ranged in size of viewership and experience to understand how they personally adapted their content to the platform of YouTube as they create videos. I find that creators create a situated practice drawing form a bricolage of information coming from many sources. I also find that this individual practice and communal practice in creator communities contributes to the process of identification. Both practice and identification are influenced by the strategy that YouTube puts in place through its complex automated systems and algorithms that incentivize creators to make content that is in line with the platform