Glacier fluctuation chronology since the latest Pleistocene at Mount Rainier, Washington, USA
Bibliographic record
Abstract
Abstract Large stratovolcanoes in the Cascade Range have high equilibrium-line altitudes that support glaciers whose Holocene and latest Pleistocene advances are amenable to dating. Glacier advances produced datable stratigraphic sequences in lateral moraines, which complement dating of end moraines. New mapping of glacial deposits on Mount Rainier using LIDAR and field observations supports a single latest Pleistocene or early Holocene advance. Rainier R tephra overlies deposits from this advance and could be as old as >11.6 ka; the advance could be of Younger Dryas age. Radiocarbon ages on wood interbedded between tills in the lateral moraines of Nisqually, Carbon, and Emmons glaciers and the South Tahoma glacier forefield suggest glacier advances between 200 and 550 CE, correlative with the First Millennium Advance in western Canada, and during the Little Ice Age (LIA) beginning as early as 1300 CE. These results resolve previous contradictory interpretations of Mount Rainier's glacial history and indicate that the original proposal of a single pre-Neoglacial cirque advance is correct, in contrast to a later interpretation of two advances of pre- and post-Younger Dryas age, respectively. Meanwhile, the occurrence of the pre-LIA Burroughs Mountain Advance, interpreted in previous work as occurring 3–2.5 ka, is questionable based on inherently ambiguous interpretations of tephra distribution.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".