Bibliographic record
Abstract
Research Article| May 01, 2022 Preface D.B. Dingwell; D.B. Dingwell Munich Search for other works by this author on: GSW Google Scholar Grant Henderson; Grant Henderson Toronto Search for other works by this author on: GSW Google Scholar Daniel R. Neuville Daniel R. Neuville Paris Search for other works by this author on: GSW Google Scholar Author and Article Information D.B. Dingwell Munich Grant Henderson Toronto Daniel R. Neuville Paris Publisher: Mineralogical Society of America First Online: 01 May 2022 Copyright © 2022 by the Mineralogical Society of AmericaMineralogical Society of America Reviews in Mineralogy and Geochemistry (2022) 87 (1): i–xix. https://doi.org/10.2138/rmg.2022.87.00 Article history First Online: 01 May 2022 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation D.B. Dingwell, Grant Henderson, Daniel R. Neuville; Preface. Reviews in Mineralogy and Geochemistry 2022;; 87 (1): i–xix. doi: https://doi.org/10.2138/rmg.2022.87.00 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 The initiative for the development of this volume arose from preliminary discussions between the editors that it had been 25 years, and a whole generation, since RIMG had dedicated a special issue to the topic of silicate melts and their many roles in materials and geological sciences. Back in 1995 silicate melts were being rediscovered as a vital component of the earth sciences in the wake of an increasing awareness of their structural complexity, the development of new experimental techniques and their application to the determination of structure and properties of these melts, as well as, the partially unexpected results... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
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 | 0.000 | 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) | 0.032 | 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".