Morphology, internal architectures, and formation mechanisms of mega-pockmarks on the northwestern South China Sea margin
Bibliographic record
Abstract
Abstract Pockmarks, as depression morphology related to fluid escape on the seafloor, are revealed by 3D seismic data on the northwestern South China Sea (SCS) margin. The pockmarks can be classified into two groups based on their various shapes in plan view: the circular group and the elongating group. These pockmarks in the study area could be defined as mega-pockmarks because their maximum diameters can reach to 7.5 km. They commonly develop more than one crater, which are called the central crater and the secondary crater. The seismic data illuminated their complicated internal architectures in the subsurface, as well as their evolution periods, such as the initiation stage, mature stage, and abandonment stage. According to the buried structures and their genesis mechanism, mega-pockmarks could be classified into linear faults-associated pockmarks and volcano-associated pockmarks. The linear fault-associated pockmarks root on the top Middle Miocene, where the linear faults are distributed. The linear faults on the top of fluid reservoir in Middle Miocene act as conduits for fluid seepage. The fluid seepage is driven by the break of balance between the hydrostatic and pore pressure. When the fluid seepage initiates, they will migrate along the linear faults, making the linear feature of pockmarks on the seafloor. Thermogenic gas from deep intervals and biogenic gas from shallow intervals may be fluid sources for the genesis of pockmarks. However, the volcanic activities control the genesis and evolution of volcano-associated pockmarks. Volcano-associated pockmarks root on the craters of volcanoes. The volcanoes underneath the pockmarks provide volcanic hydrothermal solutions, such as phreatomagmatic eruptions through the volcanic craters. The confined fluid seepages make the pockmarks exhibit a more circular shape on the seafloor. Long-term, multiepisode fluid expulsions generate the complicated internal architecture that leads to multicratered mega-pockmarks on the northwestern margin of SCS.
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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 | 0.000 | 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".