Yedoma - loess or not loess – that’s the question
Bibliographic record
Abstract
Late Pleistocene Yedoma is often described as arctic loess, but its formation is still disputed in literature. Differences of interpretation remain between researchers of western and eastern Beringia. These differences largely center on the relevance of eolian processes for Yedoma formation. Researchers working in Yukon and Alaska often characterize Yedoma silts as primarily loess. In contrast, researchers working in Siberia have proposed several hypotheses about the origin of Yedoma, including alluvial, glaciolacustrine, deltaic, proluvial/colluvial, cryogenic-eolian, nival, and polygenetic processes. \nThe polygenetic Yedoma origin combines two major processes, (1) sedimentation and (2) syngenetic freezing, which were largely controlled by similar landscape and relief characteristics, climate conditions, periglacial processes, and the occurrence of nearby sediment sources. Syngenetic freezing, including the presence of large syngenetic ice wedges, unique cryostructures of the frozen deposits as well as fossils of the late Pleistocene mammoth megafauna and tundra-steppe flora, is the overarching similarity of the Yedoma deposits. \nIn addition to huge ice wedges, the frozen sediment sequences commonly contain excess ice, with gravimetric ice contents (ratio of the mass of liquid water and ice in a sample to the dry mass of the sample, expressed as a mass percentage) of 70 to >100 wt%; this corresponds to an absolute ice content (related to the wet sample weight) of 30 to > 60 wt% for the Yedoma sediment columns. Estimating that ice wedges occupy about 50% by volume (vol%), the total volumetric ground ice content of Yedoma sequences likely varies between 65 to 90 vol%. Therefore, the major component of the Yedoma deposits is ground ice, which is the main distinction from other loess sediment deposits. \nThe clastic components of the Yedoma deposits are poorly sorted and range in grain size from dominant silt to fine--grained sand and gravel is encountered as well. Granulometric parameters differ from site to site as well as within horizons, but the grain size peaks of nearly all samples lie within the silt and fine sand range. Multi-modal grain-size distributions suggest a variety of transport processes, and underscore the importance of the re-deposition of silts with coarser grain sizes. Heavy-mineral analyses of Siberian Yedoma suggest significant differences in detrital composition between sites, indicating different local sediment sources in the hinterland. \nIn conclusion, we answer the loess-question as follows: aeolian deposition is involved in Yedoma formation, but it is neither the single nor the major mechanism of sediment deposition in western and eastern Beringia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; both teacher heads agree on what is shown here.
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".