Spatial organization of drumlins
Bibliographic record
Abstract
Abstract Ice‐sheets flowing over soft sediments produce undulations in the bed, typically of metres in relief, of which drumlins are the most abundant and widely investigated. Consensus regarding their mechanism of formation has yet to be achieved. In this paper we examine the spatial organization of drumlins in order to provide an improved description of the phenomenon and to guide hypotheses of their formation. We review the literature highlighting contradictory findings regarding drumlin spatial organization and then use this to motivate our study based on a large sample (42 488) of drumlins from Canada, Britain and Norway. Are there typical arrangements in drumlin positioning and are they organized in a regular spatial manner (patterned) or are they distributed randomly? We recognize that drumlin fields are inherently patchy and therefore apply inhomogeneous spatial statistics in order to study their distribution. This shows that whilst drumlins are occasionally randomly placed, their main state is non‐ random. They exhibit a strong and statistically significant signal of regularity across lengths scales of 100 to 1200 m. We conclude that patterning is a near ubiquitous property of drumlins. This finding of regularity demonstrates spatial self‐organization in the bedforming process with drumlins as an emergent manifestation of sub‐glacial sediment mobility. Kilometre‐scale interactions between drumlins must occur as they evolve, or interactions may arise as a consequence of growth or migration. Hypotheses or models are required that can explain the regular spacing of drumlins. We highlight three suggestions for such self‐organization: instability in the coupling of ice flow–sediment flux–bed shape; local feedback between sediment mobility and relief; and coarsening by growth or migration. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".