How did the world’s largest submarine fan in the Bay of Bengal grow and evolve at the subfan scale?
Bibliographic record
Abstract
ABSTRACT Three individual subfan-growth cycles shown to stack up over time to form the Bengal Fan were recognized. Each of them underwent the following three main evolutionary stages. Stage 1, initial channel incision and amalgamation, was responsible for forming channel-complex sets (CCSs) with lateral trajectories and concomitant amalgamation with low aggradation. Stage 2, vertical channel aggradation and the resultant creation of intrachannel lows, was responsible for generating CCSs with vertical trajectories and concomitant organized stacking with high aggradation. Stage 3, channel avulsion and concomitant upstream propagation of lobes and crevasse splays, was responsible for developing crevasse splays and lobes. These three evolutionary stages constitute a single subfan-growth cycle (i.e., an individual single channel levee--lobe system). An abrupt shift of the channel levee position separates one subfan-growth cycle from the next. Different subfan-growth cycles stacked up over time gave rise to the world’s largest submarine fan in the Bay of Bengal. The pinch-out of lobes and splays onto levees because of the channel avulsion during subfan evolutionary stage 3 created stratigraphiconlap traps with the potential for large hydrocarbon accumulations.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".