Bibliographic record
Abstract
Abstract. Vermicular Ridge Features (VRFs) comprise a series of ridges and troughs with a circular, sinuous, and anastomosing morphology composed of clast-rich sandy diamict. VRFs were first reported on the south coast of Devon Island, Nunavut, Canada, in the Dundas Harbour region. Here, we document the presence of VRFs near Mokka Fjord on Axel Heiberg Island, Nunavut, Canada. We utilize field observations, ultra high resolution LiDAR, and ground penetrating radar to characterize and compare the morphometry and sedimentology of VRFs near Mokka Fjord to other periglacial, paraglacial, and glacial landforms. VRFs near Mokka Fjord have a diameter ranging from 6 to 37 m and reach up to 1.5 m in height. They comprise clast-rich glaciofluvial sediment and till. A leading periglacial (i.e., segregation ice features/lithalsas) and glacial (i.e., ring-ridge moraines and kame/kettled terraces) origin are presented. We interpret Mokka Fjord VRFs to be an ice-marginal feature resulting from paraglacial ablation of buried glacial ice producing a hummocky ring-ridge moraine comprised of ice marginal and supra- and englacial debris. This formation mechanism would infer a largely polythermal glacial environment with limited water supply. Likely from occasional warm-based periods at the ice margins which may allow sediment output and ice burial from basal ice debris redistribution or the thinning and subsequent burial of snout ice from glaciofluvial outwash.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.621 | 0.483 |
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".