Landscape evolution and sediment delivery in a <scp>High Arctic</scp> proglacial lake, <scp>Ellesmere Island</scp>, Canadian <scp>Arctic Archipelago</scp>
Bibliographic record
Abstract
Abstract Geophysical and morphosedimentary investigations were conducted at Strathcona Lake, a High Arctic proglacial lake and its catchment connected to the Taggart Lake Glacier, northwest corner of the Prince of Wales Icefield in Ellesmere Island (eastern Canadian Arctic Archipelago). The mapping of glaciomarine landforms and units provides, together with updated radiocarbon information, a framework for catchment evolution and sediment delivery to the lake during deglaciation and glacio‐isostatically induced relative sea level fall. A staircase of deltas with descending altitudes provide evidence for a spatially diachronous timing of ice retreat from the catchments around Strathcona Lake. Swath bathymetric mapping coupled with acoustic sediment stratigraphy show draped infills with a transition from marine to rhythmically bedded lacustrine sediments produced by hyperpycnal flows. Multiproxy investigations on a set of sediment cores highlight proglacial varves interrupted by rhythmites resulting from the erosion of fluvially incised glaciomarine sediments stored in the catchment. Pluricentimetric proglacial varves formed during the last century in response to periods of intense glacial melt, notably since the 21st century. The sedimentary record suggests the varved sediments from Strathcona Lake can be used to reconstruct the melting history of the Prince of Wales Icefield. This work provides a geomorphological, sedimentological, and geochemical framework that should guide future varve‐based reconstructions of glacial and climatic variability in Ellesmere Island.
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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 | 0.001 |
| 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".