Holocene water levels of Silver Lake, Montana, and the hydroclimate history of the Inland Northwest
Bibliographic record
Abstract
Abstract The wettest portion of the interior of western North America centers on the mountainous region spanning western Montana, Idaho, British Columbia, and Alberta. Inland ranges there capture the remnants of Pacific storms. Steep east–west hydroclimate gradients make the region sensitive to changes in inland-penetrating moisture that may have varied greatly during the Holocene. To investigate potential hydroclimate change, we produced a 7600-yr lake-level reconstruction from Silver Lake, located on the Montana–Idaho border. Ground-penetrating radar profiles and a transect of four shallow-water sediment cores that were dated using radiocarbon dating and tephrachronology revealed substantial changes in moisture through time. An organic-rich mud unit indicating wet and similar to modern conditions prior to 7000 cal yr BP is overlain by an erosional surface signifying drier than modern conditions from 7000–2800 cal yr BP. A subsequent time-transgressive increase in water levels from 2800–2300 cal yr BP is indicated by a layer of late Holocene muds, and is consistent with glacier expansion and increases in the abundance of mesic tree taxa in the region. Millennial-scale trends were likely driven by variations in orbital-scale forcing during the Holocene, but the regional outcomes probably depended upon factors such as the strength of the Aleutian Low, Pacific sea-surface temperature variability, and the frequency of atmospheric rivers over western North America.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".