Systematic organization of thin-bedded turbidites in ancient deep-marine levees: Possible evidence of rhythmic pulsing in turbidity currents
Bibliographic record
Abstract
ABSTRACT Deep-marine levees are areally extensive features that border submarine channel systems and act to confine throughgoing sediment gravity flows. Compared to the adjacent channel, where episodes of erosion and bypass are commonplace, levees are mostly depositional features that experience little erosion, and therefore high preservation potential of individual beds, and as a consequence are generally assumed to provide a nearly continuous depositional record of sediment transport events down deep-marine slopes. Nevertheless, despite their size, volumetric prominence, and interpretive significance in the deep-marine sedimentary record, levees have received much less research attention compared to the adjacent channels. Exceptionally well exposed levee deposits in the Neoproterozoic Windermere Supergroup are dominated by thin-bedded, upper-division turbidites that form sharply bounded bedsets typically comprising 2–10 beds with similar grain size, bed thickness, Tc and Td/e division thickness, number of sets of ripple cross-lamination per bed, and ripple height, width, and spacing; additionally, the lithological and dimensional characteristics of the component beds in a bedset change at similar rates and spatial position along depositional strike. Such similarity suggests that deposition of each bed in a bedset is not associated with separate flow events (i.e., turbidity current), but instead represent systematic and recurring pulses or surges during a single flow event with similar hydraulic and textural conditions as they overspilled the channel margin and spread over the levee. Additionally, pulses were of sufficiently low frequency to allow the accumulation of a Td/e layer at the top of each bed and at least partial consolidation of the underlying bed. Finally, studies that have monitored and evaluated the frequency of turbidity currents in modern deep-marine systems suggest that there are a smaller number of beds, and even fewer bedsets preserved in ancient levee deposits than flow events. This suggests that many flows do not travel far enough downslope, or are of insufficient height, to result in any significant deposition on the levee. The bulk of levee strata, therefore, is likely deposited by anomalously large, pulsing flows that deposit multiple beds, but occur only once every several hundred to even several thousand years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".