Deep‐tow Seismic Investigations of Methane Hydrates
Bibliographic record
Abstract
High-resolution deep-tow multichannel seismic technology, developed by the Naval Research Laboratory, has been used to study natural gas hydrates in the marine environment. The 48-channel deep-tow system uses a 250-650 Hz source; the source and receiver array are towed approximately 300 m above the, seafloor. The combination of the geometry achieved and source frequency allows us to study the geologic structure and compressional velocities within the Hydrate Stability Zone (HSZ) with significantly greater resolution than any other available technique. The data taken with this system have revealed features that require modifications of simple models for the HSZ. For example, extensive faulting has been resolved that extends from the seafloor to the base of the HSZ. Further, compressional velocity estimates obtained from these data suggest vertical zones of elevated velocity that appear to be associated with these faults. This is consistent with chemical/hydrologic models that indicate hydrates are created preferentially where fluid flux rates are high enough to exceed saturation. Data acquired at two locations on the Blake Ridge off the east coast of the U. S. and on the Cascadia margin off the Canadian west coast exhibit significantly different seismic character, implying different manifestations of flux through the HSZ. The high-resolution seismic data indicate the need for a 3-D, dynamic model of the HSZ to more fully explain the generation and dissociation of natural gas hydrates.
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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".