Field data and till composition in the GEM-2 Rae Glacial Synthesis Activity field areas, Nunavut and Northwest Territories
Bibliographic record
Abstract
This report releases the field datasets and analytical results from targeted surficial geology studies and till sampling completed in 2017 and 2018 in mainland Nunavut and eastern Northwest Territories as part of Natural Resources Canada's Geomapping for Energy and Minerals (GEM?2) Rae Synthesis of Glacial History and Dynamics Activity in the interior of the Keewatin Sector of the Laurentide Ice Sheet. Fieldwork consisted of targeted mapping of glacial flow indicators to resolve the relative ice-flow chronology, sampling material for geochronology to help reconstruct the glacial and post-glacial histories at a regional scale, and documenting the nature and composition of the glacial sediments in various glacial terrains. In addition to the field and analytical datasets, this report provides a detailed description of the field and analytical methods. In 2017, Quaternary geological field observations were made at 92 sites; 39 till and 16 geochronology samples were collected in 5 areas in the Baker Lake and Arviat regions, Nunavut. In 2018, the focus shifted to the Healey Lake area in eastern Northwest Territories and central mainland Kitikmeot region, Nunavut. Quaternary geological field observations were made at 72 sites; 44 till and 17 geochronology samples were collected. Till samples were analysed for matrix geochemistry and texture, gold grain counts, indicator mineral picking and probing, and pebble lithology counts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.003 | 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".