Problems of ecological and technical safety by exploration and production of natural gas hydrates
Bibliographic record
Abstract
Gas hydrates - the firm crystal connections form water (liquid water, ice, water vapor) and low-molecular waterproof natural gases (mainly methane) whose crystal structure effectively compresses gas e.s.: each cubic meter of hydrate can yield over 160 m3 of methane.In present time, the exploitation of the Messoyahsk (Russia) and Mallik (Canada) deposits of gas hydrates is conducted actively. The further perfection of prospecting methods in the field of studying gas hydrates containing sediments depends on the improvement of geophysical and the well test research, among which native-state core drilling is one of the major. Sampling a native-state core from gas hydrates sediments keeps not only the original composition but structural - textural features of their construction.Despite of the appeal to use gas hydrates as a perspective and ecologically pure fuel possessing huge resources, the investigation and development of their deposits can lead to a number of negative consequences connected with hazards arising from the maintenance of their technical and ecological safety of carrying out. Scales of the arising problems can change from local to regional and even global.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".