Report of 2023 field activities for the GEM-GeoNorth West-central Keewatin Glacial Dynamics activity, Nunavut
Bibliographic record
Abstract
The landscapes we see today in northern Canada are the results of the dynamics of former continental glaciations of the Quaternary. As the environment evolved with the cyclic growth and decay of ice sheets, it is paramount to understand the history of these glacial cycles to provide a robust framework for geological and environmental studies. Much is known about these glaciations in southern Canada, but in northern Canada, extensive regions remain poorly studied because of their remoteness and hence knowledge of past glaciations there remains somewhat limited. West-central Keewatin, for example, critically lacks field data on glacial geology in many sectors. Hence, as part of the GEM-GeoNorth West-central Keewatin Glacial Activity, field investigations on the glacial geology around Lake Dubawnt in mainland Nunavut were undertaken in 2023. Here, we detail the field methodology used to compile geospatial information and measurements of ice-flow indicators, and to collect till, bedrock, boulder and sediment samples for terrestrial cosmogenic nuclide and luminescence dating. A total of 111 ground observation sites were visited, including the collection of 108 ice-flow measurements and 93 samples. Preliminary interpretations of the relative chronology and spatial relationship of iceflow indicators suggest that several distinct major ice-flow phases have impacted the region. These interpretations will be complemented with the upcoming results from till compositional data and geochronological analyses. The new field datasets will be used along with remote geomorphological mapping to improve the regional glacial history and enhance success of land-resource based decisions in this part of northern Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".