Unification of Isocon and Pearce Element Ratio Techniques in the Quantification of Material Transfer
Bibliographic record
Abstract
Research Article| November 01, 2018 Unification of Isocon and Pearce Element Ratio Techniques in the Quantification of Material Transfer Luke Hilchie; Luke Hilchie 1Volcanology and Petrology Laboratory, Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada †Corresponding author: e-mail, lukehilchie@gmail.com Search for other works by this author on: GSW Google Scholar J.K. Russell; J.K. Russell 1Volcanology and Petrology Laboratory, Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada Search for other works by this author on: GSW Google Scholar Clifford R. Stanley Clifford R. Stanley 2Department of Earth and Environmental Science, Acadia University, Wolfville, Nova Scotia B4P 2R6, Canada Search for other works by this author on: GSW Google Scholar Author and Article Information Luke Hilchie 1Volcanology and Petrology Laboratory, Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada J.K. Russell 1Volcanology and Petrology Laboratory, Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada Clifford R. Stanley 2Department of Earth and Environmental Science, Acadia University, Wolfville, Nova Scotia B4P 2R6, Canada †Corresponding author: e-mail, lukehilchie@gmail.com ☼Present address: Department of Earth Sciences, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada. Publisher: Society of Economic Geologists Accepted: 27 Jul 2018 First Online: 19 Nov 2018 Online Issn: 1554-0774 Print Issn: 0361-0128 © 2018 Economic GeologyEconomic Geology Economic Geology (2018) 113 (7): 1603–1608. https://doi.org/10.5382/econgeo.2018.4605 Article history Accepted: 27 Jul 2018 First Online: 19 Nov 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Luke Hilchie, J.K. Russell, Clifford R. Stanley; Unification of Isocon and Pearce Element Ratio Techniques in the Quantification of Material Transfer. Economic Geology 2018;; 113 (7): 1603–1608. doi: https://doi.org/10.5382/econgeo.2018.4605 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 SocietyEconomic Geology Search Advanced Search Abstract Isocon and Pearce element ratio diagrams are two means of recovering the nature and extent of material transfer processes from rock compositions. Both use the concept of a conserved property to relate changes in concentrations to extensive compositional variations. We demonstrate the fundamental commonality of the two methods and show the sole differences to be a scaling factor and the choice of graphical projection (i.e., diagram axes). We propose a modification of the isocon diagram that improves visualization of element behavior and is especially effective for dilute components that normally plot near the origin. The procedure involves transforming the mass concentration data to Pearce element ratios and then subtracting a reference rock composition from all other compositions. The former step establishes a proportionality with material transfer, and the latter step translates the data set such that the reference composition corresponds to the origin. The translated rock compositions explicitly show the material differences between each sample and the reference composition; positive values represent gains and negative values losses. Presentation of the translated ratios in a spider diagram-like figure enables straightforward visualization of geochemical variability. The algorithm proposed herein is amenable to all geochemical problems involving material transfer processes where at least one element is conserved. We demonstrate the approach by application to synthetic and real data sets. 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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".