Indium deposits in the United States
Bibliographic record
Abstract
This U.S. Geological Survey (USGS) data release provides the descriptions of the only U.S. sites-including mining districts, mineral occurrences, and mine features-that have reported production and (or) resources of indium (In). This dataset contains the Bingham and West Desert deposits in Utah, and the Chino site in New Mexico. Indium is considered a critical and strategic mineral because of its use in the aerospace, defense, energy, and telecommunications sectors. The primary applications are flat-panel displays, and specialty alloys (Fortier and others, 2018). In 2021, the U.S. was 100 percent net import reliant on indium from China, Canada, Republic of Korea, and France (U.S. Geological Survey, 2022). Indium is most commonly recovered from sphalerite, a zinc-sulfide mineral, wherein the indium occurs in quantities of less than 1 part per million (ppm) to 100 ppm (U.S. Geological Survey, 2022). In the U.S., indium is found in porphyry and skarn deposits. The West Desert deposit in Utah is the only deposit in the U.S. with a modern National Instrument 43-101 (NI 43-101) compliant resource estimate of indium (Dyer and others, 2014). The entries and descriptions in the database were derived from published papers, reports, data, and internet documents representing a variety of sources, including geologic and exploration studies described in State, Federal, and industry reports. Resources extracted from older sources might not be compliant with current rules and guidelines in minerals industry standards such as NI 43-101. The presence of an indium mineral deposit in this database is not meant to imply that the deposit is currently economic. Rather, these deposits were included to capture the characteristics of the largest indium deposits in the United States. Inclusion of material in the database is for descriptive purposes only and does not imply endorsement by the U.S. Government. The authors welcome additional published information in order to continually update and refine this dataset. Dyer, T.L., Tietz, P.G., and Austin, J.B., 2014, Technical report on the West Desert zinc-copper-indium-magnetite project, preliminary economic assessment, Juab County, Utah, prepared for InZinc Mining Ltd. [Filing date March 17, 2014]: Mine Development Associates, 188 p., accessed March 10, 2020, at http://www.sedar.com. Fortier, S.M., Nassar, N.T., Lederer, G.W., Brainard, J., Gambogi, J., and McCullough, E.A., 2018, Draft critical mineral list-Summary of methodology and background information-U.S. Geological Survey technical input document in response to Secretarial Order No. 3359: U.S. Geological Survey Open-File Report 2018-1021, 15 p., https://doi.org/10.3133/ofr20181021. U.S. Geological Survey, 2022, Mineral commodity summaries 2022: U.S. Geological Survey, 202 p., https://doi.org/10.3133/mcs2022.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".