Ice stream dynamics and ice margin retreat of the last Laurentide Ice Sheet in the Northwest Territories, Canada
Bibliographic record
Abstract
The Laurentide Ice Sheet (LIS) was the largest of the ephemeral Pleistocene ice sheets in the Northern Hemisphere, with a Last Glacial Maximum (LGM) ice volume similar to the modern Antarctic ice sheet. A recent inventory of paleo-ice streams across the LIS shows many similarities with present-day ice streaming in Antarctica, where ice streams account for approx. 90% of mass loss. However, in the Mackenzie Lowlands of the Northwest Territories, Canada, the paleo-ice stream record is enigmatic. Previous work has identified a number of large paleo-ice streams, including the Mackenzie Trough, Anderson, Bear Lake and Fort Simpson ice streams, however, their extent, configuration, temporal relationship to each other and spatial evolution over time remains poorly constrained. Consequently, their impact on the rate and style of deglaciation of the northwestern sector of the LIS is poorly understood. Here we utilise the newly available high resolution Arctic DEM (0.5 m resolution) to re-map glacial landforms across the Mackenzie Lowlands in greater detail (area >800,000 km2). We then use this landform record to reconstruct the ice dynamics in this region following the well-established approaches of flowset mapping and the glacial inversion method. The high resolution data allow us to present a detailed reconstruction of LGM ice flow over the Mackenzie Lowlands and resolve the configuration and evolution of ice streams over time. The landform record suggests that the ice streams operated time-transgressively during deglaciation, switching on and off at different times. While ice contact landforms, such as moraines, lateral and submarginal meltwater channels and ice-contact deltas, show the overall retreat of the LIS towards the Keewatin Dome in the east, in several regions the ice retreat record is complex, suggesting interlobate ice configurations with multiple ice retreat directions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".