Mineral Surface Coatings: Environmental Records at the Nanoscale
Bibliographic record
Abstract
Research Article| June 01, 2017 Mineral Surface Coatings: Environmental Records at the Nanoscale Michael Schindler; Michael Schindler 1 Department of Earth Sciences Laurentian University Sudbury, Ontario P3E 2C6, Canada E-mail: mschindler@laurentian.ca Search for other works by this author on: GSW Google Scholar David M. Singer David M. Singer 2 Department of Geology Kent State University Kent, Ohio 44242, USA E-mail: dsinger4@kent.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Michael Schindler 1 Department of Earth Sciences Laurentian University Sudbury, Ontario P3E 2C6, Canada E-mail: mschindler@laurentian.ca David M. Singer 2 Department of Geology Kent State University Kent, Ohio 44242, USA E-mail: dsinger4@kent.edu Publisher: Mineralogical Society of America First Online: 29 Nov 2017 Online Issn: 1811-5217 Print Issn: 1811-5209 Copyright © 2017 by the Mineralogical Society of AmericaMineralogical Society of America Elements (2017) 13 (3): 159–164. https://doi.org/10.2113/gselements.13.3.159 Article history First Online: 29 Nov 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Michael Schindler, David M. Singer; Mineral Surface Coatings: Environmental Records at the Nanoscale. Elements 2017;; 13 (3): 159–164. doi: https://doi.org/10.2113/gselements.13.3.159 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 SocietyElements Search Advanced Search Past and present (a)biotic soil processes can be preserved by mineral surface coatings, which can sequester contaminants in soils and sediments. The coatings can contain complex assemblages of nanometer-size minerals and organic components. The formation, composition, and morphology of these complex mineral assemblages depend on, and hence reflect, the mineralogical and chemical composition of the substrate they develop on and the environmental factors in the surrounding soils and sediments. Mineral surface coatings typically contain complex and variable porosities, many with regions of limited fluid flow. Low-flow conditions, combined with different nanometer-size phases in the interior of mineral surface coatings, allow coatings to sequester contaminant-bearing solutes, complexes, and nanoparticles. 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 | 0.001 |
| 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 | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".