AGE-EROSION CONSTRAINTS ON AN EARLY PLEISTOCENE PALEOSOL IN YUKON, CANADA, WITH PROFILES OF <sup>10</sup>BE AND <sup>26</sup>AL: EVIDENCE FOR A SIGNIFICANT LOESS COVER EFFECT ON COSMOGENIC NUCLIDE PRODUCTION RATES
Bibliographic record
Abstract
Abstract Wounded Moose type paleosols developed on remnant deposits of Late Pliocene to Early Pleistocene [pre-Reid] Cordilleran Ice Sheet [CIS] glaciations in central Yukon, Canada. It is an important regional soil-geomorphic marker at the boundary between early CIS advances and the non-glaciated regions of Yukon and Alaska. Yet, at present, its age is poorly constrained between the Reid [0.2 Ma] and earliest [2.84 Ma] CIS advances. Here, we apply depth profiles of in situ-produced cosmogenic 26Al and 10Be to obtain both a minimum exposure age [1.12+0.44/−0.36 Ma, 2σ] and maximum erosion rate [1.1+0.9/−0.5 m Myr−1] for the Wounded Moose paleosol. Our results show that this soil formed under exceptionally stable conditions [max erosion rate similar to polar bedrock erosion rates] and that it pre-dates the emergence of the 100 ka [eccentricity] climate cycle. Contrasting our results from single- and joint-nuclide depth profile models reveals a significant discrepancy between calculated and effective 10Be and 26Al production rates [40–65% of expected values]. We interpret this discrepancy as the result of intermittent loess cover—with a time-averaged depth between 60 and 110 cm—which significantly reduced apparent exposure ages obtained from the single–nuclide model. The observation of such a significant loess-cover effect on cosmogenic nuclide production has implications for exposure dating in glacial and periglacial environments; a multi-nuclide sampling strategy is required to quantify this effect.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".