The periodic topography of ice stream beds: Insights from the Fourier spectra of mega‐scale glacial lineations
Bibliographic record
Abstract
Abstract Ice stream bed topography contains key evidence for the ways ice streams interact with, and are potentially controlled by, their beds. Here we present the first application of two‐dimensional Fourier analysis to 22 marine and terrestrial topographies from 5 regions in Antarctica and Canada, with and without mega‐scale glacial lineations (MSGLs). We find that the topography of MSGL‐rich ice stream sedimentary beds is characterized by multiple, periodic wavelengths between 300 and 1200 m and amplitudes from decimeters to a few meters. This periodic topography is consistent with the idea that instability is a key element to the formation of MSGL bedforms. Dominant wavelengths vary among locations and, on one paleo ice stream bed, increase along the direction of ice flow by 1.7 ± 0.52% km −1 . We suggest that these changes are likely to reflect pattern evolution via downstream wavelength coarsening, even under potentially steady ice stream geometry and flow conditions. The amplitude of MSGLs is smaller than that of other fluvial and glacial topographies but within the same order of magnitude. However, MSGLs are a striking component of ice stream beds because the topographic amplitude of features not aligned with ice flow is reduced by an order of magnitude relative to those oriented with the flow direction. This study represents the first attempt to automatically derive the spectral signatures of MSGLs. It highlights the plausibility of identifying these landform assemblages using automated techniques and provides a benchmark for numerical models of ice stream flow and subglacial landscape evolution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".