Laurentide Ice Sheet configuration in southern Ontario, Canada during the last glaciation (MIS 4 to 2) from stratigraphic drilling and LIDAR-based surficial mapping
Bibliographic record
Abstract
Regional subsurface mapping of glacial depositional systems preserved in buried bedrock paleovalleys, and quantitative analysis of new LiDAR imagery of surface glacial landforms using machine learning techniques, when combined, are powerful tools for assessing the dynamics of the Laurentide Ice Sheet (LIS) during the last (Wisconsinan) glaciation in southern Ontario. While age dating of deposits preserved below Last Glacial Maximum tills (LGM: marine isotope stage (MIS) 2 < c.24 000 years B.P. (ybp)) is still sparse, newly available sedimentological data derived by cored drilling, combined with legacy outcrop data, identify thick (100 m+) successions of glaciolacustrine sediments and a lack of till(s), indicating that the ice sheet margin did not extend beyond the Niagara Escarpment at the western end of Lake Ontario, during the earliest phases of the glaciation (MIS 4) or the ensuing mid-Wisconsinan (MIS 3). Ice was able to extend into New York State blocking the Rome outlet to the Hudson Valley ponding deep proglacial lakes in the glacio-isostatically depressed Huron–Ontario–Erie basins recorded by thick glaciolacustrine sediments in paleovalleys. These were cannibalized by an expanding Late Wisconsinan ice sheet after ∼24 000 ybp recorded by extensive till sheets resting on a marked erosional unconformity, with drumlinized surfaces. Analysis and visualization of LiDAR data identifies discrete statistically validated flow sets of highly elongated streamlined bedforms (mega-scale glacial lineations (MSGLs)). These provide key evidence of a major reorganization of the ice sheet margin during deglaciation into lobate paleo ice streams shortly after 17 400 ybp. MSGLs are cut across earlier LGM drumlinized tills creating widespread “palimpsest” surfaces. At least two principal phases of fast ice flow can be identified, marked by large fluxes of sediment and the rapid building of large gravel and sand-dominated moraine complexes within interlobate depocentres, the largest glacial landforms in southern Ontario. Analysis of LiDAR data further reveals the common presence of DeGeer moraines where ice margins retreated in water, and iceberg scours. Future work using LiDAR mapping has the objective of fully documenting the number, extent, and timing of ice streams to enhance glaciological modelling when the ice sheet rapidly lost mass.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".