High-resolution, deep-towed, multichannel seismic survey of deep-sea gas hydrates off western Canada
Bibliographic record
Abstract
Abstract A multichannel seismic survey was carried out using the high-resolution deep-towed acoustics/geophysics system (DTAGS) to image the structure of deep-sea gas hydrates on the continental slope off Vancouver Island and to determine the velocity profile of the hydrated sediments. The high-frequency DTAGS data provide the means to estimate the frequency response of the bottom simulating reflector (BSR) that defines the base of the hydrate stability field in these sediments, over a broad frequency band from 15 to 650 Hz. The DTAGS sections resolved fine-scale layering as thin as a few meters within the hydrated zone and below the BSR, and they revealed small-scale faults and vertically oriented zones of very low acoustic reflectivity that may represent channels for upward migration of fluids or gas. Interval velocities determined from the DTAGS data indicate uniformly low values of about 1500 m/s to depths of 100 m below sea floor (mbsf), increasing to about 1850 m/s at the BSR (250 mbsf). The reflection from the BSR that is normally well defined in conventional low-frequency seismic surveys is at least twenty times weaker at the high DTAGS frequencies. The reflection coefficient-versus-frequency data support a new model for the velocity profile at the BSR that consists of a thin, 4–8-m layer at the BSR in which the velocity decreases by 250 m/s. The thin transition layer at the BSR implies relatively high methane flux rates of at least 1.5 mm/year.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".