Characterization, Appraisal, and Economic Viability of Alaska North Slope Gas Hydrate Accumulations”, presented at
Bibliographic record
Abstract
The collaborative research program will help determine if gas hydrate accumulations can become an economic unconventional energy resource, initially in the onshore Alaska North Slope (ANS) arctic region beneath permafrost and existing production infrastructure. The cooperative research venture between BP Exploration (Alaska), Inc. (BPXA) and the U.S. Department of Energy (DOE) facilitates high levels of collaboration between industry, government, and university researchers. The mutually beneficial research activities would not otherwise have been independently conducted by industry. Collett (1998) estimates that up to 590 TCF in-place ANS gas resources may be trapped in clathrate hydrates. An estimated 44 to 100 TCF in-place ANS gas resources may occur beneath existing infrastructure (Collett, 1993). If a significant portion of this estimated in-place gas can be economically recovered, this unconventional resource could become an important part of future gas resource development in Alaska. Gas from gas hydrates may help fill the projected future gap in U.S. domestic gas production. Other options include opening additional areas to exploration and production, increasing LNG imports, developing remote arctic regions conventional gas (Alaska and Canada) and/or developing other unconventional gas resources such as coalbed methane, tight gas, and shale gas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".