Palaeo‐ice streams and the subglacial landscape mosaic of the North American mid‐continental prairies
Bibliographic record
Abstract
The analysis of the glacial landscape of southern Saskatchewan (Canada) through multiple data sets (e.g. digital elevation model, till compositional data) has revealed previously unrecognized subglacial sediment–landform assemblages. A southwest‐trending corridor of mega‐scale till lineations (Maskwa corridor) bounded on each side by hummocky terrain extends from the Canadian Shield to southwestern Saskatchewan. This landform assemblage is clearly cross‐cut by a broad south to southeast trending corridor (Buffalo corridor) consisting of subparallel curvilinear till ridges. The carbonate content of the surface till is spatially consistent within these assemblages, suggesting a strong sediment–landform relationship. The two corridors are interpreted as the product of palaeo‐ice streams. The Maskwa palaeo‐ice stream flowed up the regional slope and across preglacial valleys, indicating it was thick and stable. Narrow dispersal trains extending across as well as down‐glacier from the Athabasca Basin suggest that the Maskwa palaeo‐ice stream extended far into the ice sheet across contrasting shield and platform terrains. In comparison, the Buffalo palaeo‐ice stream was thinner and largely controlled by subglacial geology and topography. Its catchments were located at the Canadian Shield boundary and the system was oriented along‐slope. It experienced lateral shifts and it was fed by a network of tributaries. The glacial dynamics shift from the Maskwa to the Buffalo system occurred at about 13.5 14C kyr BP. The Buffalo system later evolved into thin outlet lobes until final deglaciation of the area. The proposed model has implications for ice‐sheet reconstruction and the assessment of till properties in the prairies and in similar terrains.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".