Ice-marginal terrestrial landsystems: Sediment heterogeneity, architecture and hydrogeological implications
Bibliographic record
Abstract
Previously glaciated landscapes often present unique challenges for hydrogeological investigations. Specifically, ice-marginal terrestrial landsystems are often difficult to characterize and model considering the dynamic nature of the ice and associated meltwater and sediment gravity flow processes that result in heterogeneous sediment successions and architectures over a range of scales. This paper integrates the many advances in our understanding of glacial geology with a focus on its hydrogeological implications. Ice-marginal terrestrial landsystems can be conceptualized as complex arrangements of glacial conditions that vary as the ice margin stagnates or fluctuates over time. Subglacial, englacial, proglacial, glaciofluvial, glaciolacustrine and gravitational or glacitectonic deformation processes lead to erosional and depositional elements that stack over time to form complex subsurface successions with uncertain lateral variability. The geomorphology and sediments at surface within an area are the last expression of those erosional and depositional elements over time. The nature and architecture of sediment types expected in eight different settings are reviewed and their hydrogeological significance discussed. The evolution of a contaminated site's conceptual model is then used to demonstrate how detailed sedimentological and stratigraphic characterization of glacial successions together with an understanding of ice-marginal landsystems, can lead to a more robust site conceptual model of hydraulic conductivity architecture that can better constrain hydrogeological investigations.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".