METHANE HYDRATE STUDIES: DELINEATING PROPERTIES OF HOST SEDIMENTS TO ESTABLISH REPRODUCIBLE DECOMPOSITION KINETICS.
Bibliographic record
Abstract
The use of methane hydrate as an energy source requires development of a reliable method for its extraction from its highly dispersed locations in oceanic margin sediments and permafrost. The high pressure (up to 70 MPa) and low temperature (272 K to 278 K) conditions under which hydrates are stable in the marine environment can be mimicked in a laboratory setting and several kinetic studies of pure methane hydrate decomposition have been reported. However, the effect of host sediments on methane hydrate occurrence and decomposition are required to develop reliable hydrate models. In this paper, we describe methods to measure sediment properties as they relate to pore-space methane gas hydrate. Traditional geotechnical techniques are compared to the micrometer level by use of the synchrotron Computed Microtomography (CMT) technique. CMT was used to measure the porosity at the micrometer level and to show pore-space pathways through field samples. Porosities for three sediment samples: one from a site on Georges Bank and two from the known Blake Ridge methane hydrate site, from different depths below the mud line were measured by traditional drying and by the new CMT techniques and found to be in good agreement. The integration of the two analytical approaches is necessary to enable better understanding of methane hydrate interactions with the surrounding sediment particles.
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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 | 0.000 | 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) | 0.001 | 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".