Bibliographic record
Abstract
Announcement| April 01, 2012 New Mineral Names* Kimberly T. Tait Kimberly T. Tait † Department of Natural History, Royal Ontario Museum, 100 Queens Park, Toronto, Ontario M5S 2C6 Canada †E-mail: ktait@rom.on.ca Search for other works by this author on: GSW Google Scholar American Mineralogist (2012) 97 (4): 759–761. https://doi.org/10.2138/am.2012.593 Article history first online: 02 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation Kimberly T. Tait; New Mineral Names. American Mineralogist 2012;; 97 (4): 759–761. doi: https://doi.org/10.2138/am.2012.593 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentBy SocietyAmerican Mineralogist Search Advanced Search The following new minerals are discussed in this issue: långbanshyttanite, pseudolyonsite, and yangzhumingite. These new minerals have been described in the European Journal of Mineralogy and are reported here. N.V. Chukanov, I.V. Pekov, E. Jonsson, N.V. Zubkova, Y.E. Filinchuk, D.I. Belakovskiy, and D.Yu. Pushcharovsky (2011) Långbanshyttanite, a new low-temperature arsenate mineral with a novel structure from Långban, Sweden. Eur. J. Mineral, 23, 675–681. The new mineral långbanshyttanite was discovered in a specimen from the Långban mine Filipstad district, Värmland County, Bergslagen ore province, Sweden. The carbonate-hosted Långban deposit (59.86°N, 14.27°E) is, together with related occurrences in the western part of... You do not currently have access to this article.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.628 | 0.486 |
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".