A statistical technique for determining the source area of glacially transported granite erratics in the Queen Elizabeth Islands, Nunavut
Bibliographic record
Abstract
This paper develops a technique that utilizes spatial and compositional trends in granite erratics distributed across the eastern and northwestern Queen Elizabeth Islands to discriminate between glacial dispersal trains originating from the Precambrian Shield of Ellesmere Island and the Canadian mainland. The distribution of glacially transported granite erratics in the eastern and northwestern Queen Elizabeth Islands defines a coherent pattern of regional dispersal from the Precambrian Shield of eastern Ellesmere Island. Principal components and cluster analyses demonstrate that most erratics within this dispersal train cluster within the same compositional group. Other members of this group represent outcrops on eastern Ellesmere Island, which define the locations of possible source areas. However, other compositional groups, which are unique to outcrops on the mainland, are absent from this dispersal train. Collectively, these spatial and compositional trends suggest that granite erratics on southwest Ellesmere, Amund Ringnes, and Meighen islands occur within a single dispersal train that resulted from the westward expansion of the Innuitian Ice Sheet from the Precambrian Shield of eastern Ellesmere Island. This technique may determine what differences, if any, exist among the composition of granite erratics deposited by the westward expansion of the Innuitian Ice Sheet across the Queen Elizabeth Islands and those deposited by the northward expansion of the Laurentide Ice Sheet. Any such differences may be useful in determining whether granite erratics of presently unknown provenance elsewhere in the Queen Elizabeth Islands are of Laurentide or Innuitian origin.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".