Little tools, big job: The periglacial conveyor system in cryoplanated uplands
Bibliographic record
Abstract
Abstract The mechanisms of sediment removal associated with the nivation process suite are underinvestigated, a situation that hinders development of a unified, coherent theory of cryoplanation terrace formation. This study links sorted stripes—a type of periglacial patterned ground frequently encountered on cryoplanation terrace treads—to active hydrologic networks capable of transporting large quantities of fine sediments on periglacial hillslopes. Traditional interpretations hold that the presence of sorted patterned ground indicates geomorphic quiescence, a view that has contributed to the dismissal of these features as a factor in the formation of erosional periglacial topography. We address the geomorphic role of sorted stripes as fluvial features by investigating their hydrologic potential for transporting weathered material across and off developing cryoplanation terraces. Flow modeling and watershed geomorphometric analyses were conducted using a high‐resolution digital elevation model of a large cryoplanation terrace in a geomorphically active periglacial upland near Atlin, British Columbia, Canada. Results demonstrate the landscape‐scale spatial organization and geomorphic effectiveness of sorted‐stripe networks—“little tools”—for transporting water and suspended sediment across large cryoplanated surfaces. We present a qualitative model of sediment production and transportation, “the periglacial conveyor system,” that outlines erosional processes responsible for cryoplanation terrace formation and defines the distinctive hydrologic–geomorphic imprint imparted by sorted stripes on periglacial hillslopes.
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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 | 0.001 |
| 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".