Streamlined hard beds formed by palaeo-ice streams: A review
Bibliographic record
Abstract
Fast-flowing ice streams occur within modern ice sheets and also operated in Pleistocene ice sheets. The reconstruction of palaeo-ice streams normally relies on the mapping of mega-scale glacial lineations (MSGLs) and drumlins composed of soft sediment, mainly till. Analysis of new satellite imagery and digital terrain models, demonstrates the presence of large fields of kilometre-scale glacial lineations comprising rock drumlins, megagrooves and megaridges. In this paper we describe and analyse a number of such ‘hard-bed’ landform systems from the former Laurentide and British–Irish ice sheets, occurring in a variety of palaeo-ice stream settings. These are attributed to erosion of crystalline and sedimentary rock below fast flowing ice streams. Bedrock properties such as hardness, fracture spacing and bedding and their orientation with respect to ice flow have a profound effect on the occurrence and character of elongate rock bedforms. Elongate streamlined forms on hard crystalline rock, as on the Canadian Shield, only form under special circumstances; in contrast, sedimentary strata are highly susceptible to form streamlined hard beds, specifically if bedrock strike is parallel to ice flow. Large-scale elongate rock bedforms are erosional in origin, formed by preferentially focused abrasion or by lateral plucking, depending on bedrock type. Many palaeo-ice stream footprints previously mapped in the Laurentide Ice Sheet on the basis of soft-bed bedforms are shown to be significantly larger, extending up-ice across sedimentary strata and onto Precambrian crystalline rocks. Hard-bed streamlined forms further show that ice streaming does not necessitate a deformable bed, but can equally occur on smooth hard beds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".