Subglacial landforms in northern Manitoba, Canada, based on remote sensing data
Bibliographic record
Abstract
Please click here to download the map associated with this article. This paper presents a new subglacial landform map for northern Manitoba (58°-60° N). The region was formerly covered by the Laurentide Ice Sheet and is located at the southern margin of the Late Wisconsinan (∼25-10 Ka BP) deglacial Keewatin Ice Divide just west of Hudson Bay. Mapping was focused on determining the location and orientation of streamlined landforms (drumlins and megaflutes), Rogen moraines, and eskers for the 109,366 km2 region. Based on the theory that landforms such as drumlins and Rogen moraines all result from subglacial ice flow processes, this map forms the basis for reconstruction of ice flow sets that indicate past glacial phases in northern Manitoba. It shows that the geomorphologic record, and hence ice flow history, is more complex than previously reported. There are several successive generations of ice flow indicators superimposed on top of each other, sometimes at abrupt (90°) angles. Special attention is paid to the location and ridge crest orientation of Rogen moraines in northern Manitoba. Hence the map also provides insights into the characteristics of Rogen moraines in northern Manitoba, which are critical for investigating formative processes. 11,007 individual landforms were mapped using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery in combination with a Shuttle Radar Topography Mission (SRTM) digital elevation model and several SPOT 4 satellite images. The results are presented as a printable map at 1:1,125,000 scale.
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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 | 0.003 | 0.004 |
| 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) | 0.003 | 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".