GAS METHANE HYDRATES-RESEARCH STATUS, ANNOTATED BIBLIOGRAPHY, AND ENERGY IMPLICATIONS
Bibliographic record
Abstract
The objective of this task as originally conceived was to compile an assessment of methane hydrate deposits in Alaska from available sources and to make a very preliminary evaluation of the technical and economic feasibility of producing methane from these deposits for remote power generation. Gas hydrates have recently become a target of increased scientific investigation both from the standpoint of their resource potential to the natural gas and oil industries and of their positive and negative implications for the global environment After we performed an extensive literature review and consulted with representatives of the U.S. Geological Survey (USGS), Canadian Geological Survey, and several oil companies, it became evident that, at the current stage of gas hydrate research, the available information on methane hydrates in Alaska does not provide sufficient grounds for reaching conclusions concerning their use for energy production. Hence, the original goals of this task could not be met, and the focus was changed to the compilation and review of published documents to serve as a baseline for possible future research at the Energy & Environmental Research Center (EERC). An extensive annotated bibliography of gas hydrate publications has been completed. The EERC will reassess its future research opportunities on methane hydrates to determine where significant initial contributions could be made within the scope of limited available resources.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.043 | 0.080 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".