Late pleistocene glacial and environmental history of the Skagit valley, Washington and British Columbia
Bibliographic record
Abstract
Drainage patterns established in the Tertiary in the North Cascades were reorganized to accommodate southern drainage of Cordilleran Ice Sheet meltwater. Repeated continental glaciation rendered the Skagit an interconnected valley, with meltwater routes opening it to the Fraser and Okanogan watersheds, and linking it to a drainage system around the east margin of the Puget lobe of the ice sheet. Alpine glaciers from two major tributaries blocked Skagit valley during the late Wisconsin Evans Creek stade, creating glacial lakes Concrete and Skymo. Organic material from lake sediments provides the first radiometric constraint on the beginning of the Evans Creek stade in the Cascades about 25,040 14C yr BP. Sediments and macrofossils at the Cedar Grove section define two advances of Baker alpine glaciers during this stade, separated by a period of warmer and wetter climate at 20,310 14C yr BP. During colder parts of the Evans Creek stade macrofossils indicate treeline was as much as 1200 150 m lower than present, which corresponds to a mean July temperature depression of approximately 7 1˚C. Glacier equilibrium line altitudes (ELA) during the cold periods were depressed 730-970 m below the modern glaciation threshold. Skagit valley alpine glaciers advanced several times to positions 5-10 km below valley heads between 12, 200 and 9,975 14C yr BP. ELA depression during these advances vary from 340 ± 100 m to 590 ±75 m, with greater depression in maritime western tributaries. Skagit ELA depression values are about 200 m less than reported for the southern North Cascades during the Sumas stade. The effect of the Cordilleran Ice Sheet on precipitation likely caused ELAs to be higher in the Skagit valley than in the southern North Cascades.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".