The Influence of Topography and Sediment Cover Change on Pleistocene Glacial Cycles and the MPT with Coupled Ice Sheet-Climate-Sediment Physics
Bibliographic record
Abstract
<!--!introduction!--> A change from a low to high friction bed under the North American Ice Complex through the removal of pre-glacial regolith has been hypothesized to play a critical role in the mid-Pleistocene transition from 41 to 100 kyr glaciations. However, this regolith hypothesis requires constraint on pre-glacial regolith cover and topography, mechanistic constraints on what amount of regolith can be removed, and complete process coupling to infer the net effect from topography and sediment changes. This landscape evolution has not yet been simulated for a realistic, 3D North American ice sheet fully considering basal processes (e.g. sedimentary, basal hydrology, and the solid earth response to changing sediment and bedrock load). Constraints of the pre-glacial bed are sparse and the bounds are wide. What constraint does the present day sediment distribution offer and how do topography and sediment change influence glacial cycles? Using varied pre-glacial topographies, sediment thicknesses, and fully coupled climate, ice, sediment and subglacial hydrology model parameterizations, we show the constraint on mean pre-glaciation sediment thickness provided by the present day surface sediment distribution and regional estimates of bedrock erosion. More broadly, we find that this landscape evolution has a strong influence on the strength and duration of early Pleistocene glaciations. The ice, climate, and sediment processes encapsulated in this fully coupled Earth systems model capture the evolution of the Pleistocene North American glacial system: the 41 to 100 kyr glacial cycles transition, early Pleistocene extent, sea level change, last deglacial margins, and broad present-day sediment distribution within uncertainty.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".