Bibliographic record
Abstract
The Laurentide Ice Sheet (LIS) was the largest ephemeral ice sheet in the Northern Hemisphere, reaching its all-time maximum during the last glacial cycle (~115 ka to ~11.7 ka) as it coalesced with the Cordilleran and Innuitian ice sheets over northern North America and the Canadian Arctic Archipelago. At its maximum extent it was comparable in size to the modern-day Antarctic Ice Sheet and may provide a useful analogue for understanding the long-term dynamics of ice sheets. There are considerable regional variations in our understanding of the deglaciation of the LIS. In particular, the northwestern LIS remains one of the most poorly understood sectors, as the latest reconstruction of this sector dates to the early 1990s and empirical constraints on the timing of deglaciation are sparse. In this thesis, I reconstruct the deglaciation of the northwestern LIS from its local Last Glacial Maximum (LGM) position using numerical dating methods and glacial geomorphological mapping. I use a combination of high-resolution digital elevation models (DEMs) and satellite imagery to map the glacial geomorphology of much of the Northwest Territories, Canada, and reconstruct the ice margin retreat patterns, ice flow dynamics, and interaction of the northwestern LIS with other ice masses. This new information is...
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".