Mineral systems, their types, and distribution in nature. I. Khibiny, Lovozero, and the Mont Saint-Hilaire
Bibliographic record
Abstract
In accordance with the set of species-defining chemical elements in minerals, n -component systems (where n = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) for all mineral species (4952) known to 2014 inclusive were distinguished. Seventy chemical elements have been established to be species-defining, which are distributed by mineral systems as follows: 1 (29), 2 (62), 3 (68), 4 (61), 5 (61), 6 (55), 7 (49), 8 (38), 9 (28), and 10 (19). The number of mineral species in which certain chemical elements are species-defining has been specified. Oxygen (4041), hydrogen (2755), silicon (1448), calcium (1139), sulfur (1025), aluminum (960), iron (917), sodium (914), copper (616), phosphorous (580), arsenic (575), and magnesium (550) are the leading elements in minerals in the Earth’s crust. It has been found that the most species-defining elements are normally distributed by mineral systems. The distributions of mineral species in various systems from the Khibiny and Lovozero, Kola Peninsula, Russia; and Mont Saint-Hilaire, Quebec, Canada peralkaline plutons were compared and the characters of species-defining element distribution in these localities were compared. Si, Na, K, C, F, Ti, Ce, Zr, Nb, Sr, and Th are “excess” species-defining elements in minerals from the plutons compared to the total number of mineral species, whereas S, Cu, Pb, Cl, B, Te, Ag, Ni, and Be are “scarce” elements.
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) | 0.000 | 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".