Late Holocene glacial history of Scimitar Glacier, Mt. Waddington area, British Columbia Coast Mountains, Canada
Bibliographic record
Abstract
Scimitar Glacier originates below the northeast face of Mt. Waddington in the southern British Columbia Coast Mountains and flows 18 km down valley to calve into a proglacial lake. At several locations, downwasting of the glacier surface has exposed stacked till units separated by wood-bearing horizons in the proximal slopes of lateral moraines flanking the glacier. Historical moraine collapse and erosional breaching has also revealed the remains of standing trees buried in moraine-dammed lake sediments. Radiocarbon and tree-ring dating show that Scimitar Glacier expanded down valley at least three times in the late Holocene. The earliest evidence found for ice expansion indicates Scimitar Glacier was advancing in 3167–2737 cal years BP in association with the regional Tiedemann Advance. Following this advance, the glacier downwasted prior to expanding in 1568–1412 cal years BP during the First Millennial Advance. A final period phase of moraine construction was initiated during late Little Ice Age glacial expansion before A.D. 1742 and extended until at least A.D. 1851, after which Scimitar Glacier began to recede and downwaste. This record is comparable to that recorded at other glaciers in the southern British Columbia Coast Mountains and confirms the long-term relationship between regional climate trends and glacier behaviour in this setting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".