Carbonic nanostructures in subsurface rocks: problem review Part I. Fullerenes
Bibliographic record
Abstract
The paper deals with the review of the results of detection and analysis of fullerenes in natural objects. The fullerenes (generally, buckminsterfullerenes С60) were revealed in hard subsurface rocks and sedimentary deposits of Cretaceous-Paleogene, Perm and Pre-Cambrian stages of the Earth. The map of the Earth regions of fullerene exploration and the data on fullerene composition in the rocks is provided as well. The concepts of both biogenic and abiogenic fullerene origin are known. In the first case, the process of slow metamorphization of putrid mud and terrestrial crop took place under the impact of compressing and temperature, as a result of which various allotrope compounds of hydrocarbon dispersed in the mineral matrix were formed and accumulated. In the second case, the formation of fullerenes took place due to the shocking impact during thunderbolt or fireballs (Sudbury meteorite, carbonic chondritic meteorites) strikes on the rocks of earth surface, as well as global forest fires. For reliable fullerene identification in the samples of sedimentary and subsurface rocks should be used only physical-chemical methods of high definitions, such as laser desorption / ionization and electric-shocking mass-spectrometry. In the natural objects is predominantly revealed fullerene С60.Other types of fullerenes - C70, C74, C78, C84 and C100 are identified more rarely. A hypothesis on the composition of carbonic nanostructures in the rocks of mud volcanoes in the aspect of obtained information is developed.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".