Highly Siderophile and Strongly Chalcophile Elements in Magmatic Ore Deposits
Bibliographic record
Abstract
Research Article| January 01, 2016 Highly Siderophile and Strongly Chalcophile Elements in Magmatic Ore Deposits Sarah-Jane Barnes; Sarah-Jane Barnes Sciences de la Terre, Université du Québec à Chicoutimi, Chicoutimi, Québec, G7H 2B1, Canada, sjbarnes@uqac.ca Search for other works by this author on: GSW Google Scholar Edward M. Ripley Edward M. Ripley Department of Geological Sciences, Indiana University, Bloomington Indiana, 47405, USA, ripley@indiana.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Sarah-Jane Barnes Sciences de la Terre, Université du Québec à Chicoutimi, Chicoutimi, Québec, G7H 2B1, Canada, sjbarnes@uqac.ca Edward M. Ripley Department of Geological Sciences, Indiana University, Bloomington Indiana, 47405, USA, ripley@indiana.edu Publisher: Mineralogical Society of America First Online: 09 Mar 2017 © 2016 Mineralogical Society of America Reviews in Mineralogy and Geochemistry (2016) 81 (1): 725–774. https://doi.org/10.2138/rmg.2016.81.12 Article history First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Sarah-Jane Barnes, Edward M. Ripley; Highly Siderophile and Strongly Chalcophile Elements in Magmatic Ore Deposits. Reviews in Mineralogy and Geochemistry 2016;; 81 (1): 725–774. doi: https://doi.org/10.2138/rmg.2016.81.12 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyReviews in Mineralogy and Geochemistry Search Advanced Search An ore deposit by definition must be economically viable, that is to say it must contain sufficient material at high enough grade to make it possible to mine and process it at a profit (Bates and Jackson 1987). This requires the elements to be collected and concentrated by some phase and for them to be deposited close to the surface of the earth. At the oxygen fugacities found in the crust, native Fe is not normally stable and thus the highly siderophile elements (defined as Ru, Rh, Pd, Re, Os, Ir, Pt, and Au) cannot behave as siderophile... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".