An innovative method for creating and using nanoparticles for gas extraction from gas hydrates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The growth of prices for traditional energy sources prompts Ukraine to seek new approaches to solving energy problems. Today, the country has intensified its work in this direction, in particular, legislative support is being developed and improved, and the investment climate for alternative energy projects is improving. In many countries of the world, it has long been understood how serious and necessary is the development of alternative energy. At present, in the face of various gas contradictions and unstable oil prices, the need for energy carriers is constantly increasing, which makes it necessary to seek the latest solutions to the energy problem. Many leading countries in the world are engaged in the search for alternative sources of energy, one of which is natural gas hydrates. This relatively new resource offers great opportunities both for economic growth and stability of states, and for the development of scientific institutions in this field. Flagships in the study and development of gas-hydrated deposits are the United States, China, Japan and Canada. Along with them should be noted the achievements of scientists in India, EU countries, Ukraine, Russia and Bulgaria.
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.
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 it